journal jan-june 2016

January-June 2016 Vol. 7, No. 1 ISSN 0975-9514

AKGEC International Journal of Technology

Ajay Kumar Garg Engineering College

CONTENTS

Patron-in-ChiefDr. R.K. Agarwal

Editor-in-Chief Dr. Ranjit Singh

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Address forcorrespondence

Pre Bond Through Silicon Vias (TSVs) Testing in 3D ICs 1Abdul Manan

Hybridisation of PTS-Clipping Techniques to Progress 7PAPR in MIMO-OFDM SystemsRaj Lakshmi Shukla and Monika Singh

Electricity Generation due to Vibration by Boots 13Vaibhav Sharma and Mohini Preetam Singh

Kinematic Modeling of a Multi-Fingered Robotic Hand- A Review 17M.Z. Hussain and Dr. M. Suhaib

Overview on Burr Formation, Simulation and Experimental 24Investigation of Burr size - based on Taguchi Design of Experiments during Drilling of Alluminium 7075 Alloy Reddy Sreenivasulu and Chalamalasetti Srinivasa Rao

An Empirical Investigation of the Various Antecedents 31of the Customer Satisfaction in Case of Mobile Services - A Comprehensive Study of Haryana Province in India Vishal Garg

Design Optimization of IC Engine Rocker-Arm Using Taguchi 38Based Design of ExperimentsDr. Goteti Chaitanya and Reddy Sreenivasulu

Latest Trends in Communications 43Manjit Singh

Factors Influencing the Adoption of Internet Banking in 51Selected Banks of Ethiopia - A Study Dr. Girish Kumar Painoli

Vibrational Study of Aspartic Acids 60Dr. Santosh Kumar

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Pre BondThrough Silicon Vias (TSVs) Testing in 3D ICs

Abdul MananDepartment of Electrical and Electronics Engineering, G D Goenka World Institute

– Lancaster University Gurgaon, [email protected]

Abstract — 3-D Integrated Circuits (IC’s) offer many advantages like higher device density, higher bandwidth, low-power, and smaller form-factor. Testing the integrity of interconnects realized by through silicon vias (TSVs) in 3-D integrated circuits (3-D IC) is considered a challenging task. TSVs are excessively small and fragile for current probe technology. Just like other components, the fabrication and bonding of TSVs can fail. A failed TSV can severely increase the cost and decrease the yield as the number of dies to be stacked increases. Author describes the on-die test architecture and probe technique needed for TSV testing, in which individual probe needles make contact with multiple TSVs at a time. Simulation results using LTSPICE are presented for a TSV network. It is demonstrated that one can achieve high resolution in these measurements and therefore high accuracy in defect detection when one or multiple TSVs at a time are targeted.

Keywords: Integrated Circuits; Through silicon vias (TSVs); Die; Simulation.

I. INTRODUCTIONLOW power and high speed requirements keeps on pushing the semiconductor industry towards various innovative ideas and methodology. By doubling the number of transistors on a die every two years, chip makers have given us ever more powerful PCs and electronic gadgets at prices that shrink almost as fast as transistors do. So it may come as a surprise to many that today wires, not transistors, are determining the performance and cost of microchips [1]. Three Dimensional 3-D stacking technology has the potential to keep pace with the performance improvement projected by Moore’s law. Three Dimensional Integrated circuits (3D IC’s) reduce interconnects length by stacking multiple dies in a single package and smaller form factor. The length of global wires can be reduced by as much as 50%, wire-limited clock frequency can be increased by 3.9X, and wire-limited area can be decreased by 84% [2], [3]. Power can be reduced by 51% at the 45-nm technology node [3], [4]. In 3-D ICs, gates are placed in multiple dies, and the dies are stacked vertically on top of each other as illustrated in Figure 1. Since gates are distributed in multiple dies, the footprint area of each die of a 3-D IC becomes smaller than that of the circuit designed in 2-D. A smaller footprint area results in shorter total wirelength in 3-D ICs than in 2-D ICs [5], [6], [7]. Therefore,

3-D ICs have a high potential to improve the performance [7], [8], [9]. Shorter wirelength can also reduce interconnect power and improve routing congestion. Less routing congestion can in turn reduce the number of metal layers used for routing in each die of a 3-D IC, and the reduction of the metal layer count can contribute to cost reduction [10].

Figure 1. Cross-section of 3D IC.

II. THROUGH SILICON VIASA. Fabricating TSVs: The functionality of 3-D integrated circuit (IC) strongly depends on the fidelity of signals through through-silicon vias (TSVs). A TSV is a vertical electrical connection passing through a silicon die. TSVs are copper vias with diameters that may range from 1 to 30 microns [11]. As the TSV process is not a perfect one, defects can be created while forming the TSVs before bonding (assuming a via-first process) or while bonding different dies together. The defect can be created by short through the oxide surrounding the TSVs resulting in finite resistance between TSV and substrate. The open defects or ruptures can also be created during TSV growth. The non-conformal growth of the insulator also creates defects or variation in TSV properties. At the post-bond stage, the defects can be created due to variation in the resistance of the bonding material or misalignment [12].

TSV testing can be separated into two distinct categories: pre-bond testing and post-bond testing. Pre-bond testing is directed to detecting defects that are inherent in the manufacture of the TSV itself, such as impurities or voids, while post-bond testing is directed to detecting faults caused by thinning, alignment, and bonding.

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AKGEC INTERNATIONAL JOURNAL OF TECHNOLOGY, Vol. 7, No. 1

Figure 2a illustrates a microvoid defect and a pinhole defect, respectively, of a TSV. A TSV is disposed in the substrate and can take the form of a metal pillar. The TSV may be formed by etching the substrate to form a deep via or trench, depositing a barrier material in the deep via or trench, and then depositing the material forming the TSV. When depositing the material forming the TSV in the deep via or trench, a microvoid, may occur in the TSV. This microvoid increases the resistance of the TSV. The pinhole defect may occur from uneven forming of the barrier material and causes leakage between the TSV and the substrate, increasing the TSV capacitance.

Various built-in self-test (BIST) methods have been proposed in the literature to address the challenges of test development for 3-D ICs [14], [15]. Implementation of BIST for a large number of TSVs requires a considerable die area. Current

probe technology using cantilever or vertical probes requires a minimum pitch of 35μm.

They exert excessive vertical force on contact surface causing scrub marks and structural deformation. Moreover, they require large contact pads added to TSVs to ensure the connectivity [16]. A flexible membrane probe card with embedded metal probes has been proposed in the literature to probe TSVs [17]. In [18], Noia and Chakrabarty presented a DFT method for prebond testing in which individual probe needles contact multiple TSVs that are shorted together to form a network of TSVs. In this method, the capacitance and resistance of each TSV in the TSV network are determined to identify faulty TSVs.

Author presents a low-overhead digital test structure based on scan flip-flops (FFs) that detects the resistive defects in TSVs. Scan flip-flops (FFs) is implemented with 32 nm predictive technology model (PTM) [19] to be close to simulation program with integrated circuit emphasis (SPICE). The proposed model is verified to be applicable to various device models such as 32 nm PTM high-k/metalgate model.

Testing of TSVs: One basic approach to 3D-IC testing involves performing a post-bond test after each die has been bonded to the stack. The goal is to test portions of the system that could have been damaged during the bonding process. Because it is not viable to “un-bond” a die subsequently found to be defective, one study [20] maintains that performing a separate pre-bond (i.e., standalone) test to identify a Known Good Die (KGD) for stacking is more cost-effective than relying solely on post-bond testing to identify a defective die that has already rendered the entire system defective.

However, the economics of pre-bond testing have yet to be fully characterized, and one of the key challenges is how to apply the KGD test. With the exception of the bottom die, no probe pads exist for pre-bond testing because all the I/Os are accessible only through TSVs topped by fine-pitch micro-bumps, which are arrayed on both sides of the die.

Standard probe equipment applies tests only on a single side and even state-of-the-art production systems do not meet the fine-pitch and I/O bandwidth requirements of 3D-ICs. Moreover, it is difficult to perform pre-bond tests without damaging the micro-bumps or deforming the thinned wafers [21].Efforts are underway to deliver probe systems that facilitate probing on fine-pitch micro-bumps. Rocking Beam Interposer (RBI) technology [22] in membrane probe cards improves probing accuracy and minimizes bond pad damage. Contactless probing [23] may also prove viable.

At this time, however, these solutions are still a work-in-progress for meeting 3D-IC probing requirements. Likewise,

There are a number of pre-bond defects that can impact chip functionality. These include incomplete metal filling (or microvoids) in the TSVs, which increase resistance and path delay; partial breaks in the TSV, which result in a resistive path; and complete breaks in the TSV, which result in an open path. In addition, impurities in the TSV may also increase resistance and interconnect delay; and pinhole defects can lead to a leakage path to the substrate, with a corresponding increase in the capacitance between the TSV and the substrate. [13]

Figure 2a. Microvoid and Pinhole TSV defect.

Figure 2b. Top cross-sectional view of a TSV surrounded by the dielectric (SiO2), the Si depletion region, and the bulk Si.

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A REVIEW ON SUPERCAPACITORS

the test challenges specifically related to the handling of thinned wafers and thinned dies remain formidable [21, 24], and in 2010, SEMI created a taskforce specifically to define requirements and develop standards for the reliable handling and shipping of thin wafers.

Although there are new failure mechanisms due to defects caused by wafer thinning and by TSV filling, alignment, and bonding, their fault effects appear to be the same as those encountered in two-dimensional (2D) designs. Therefore, conventional stuck-at and transition-delay automatic test pattern generation (ATPG) can be used or extended to test 3D-ICs. For example, slack-based transition delay tests that target small delay defects and bridging tests that target bridging faults are already in use today to meet ultra-high test quality requirements. With the advent of 3D-ICs that offer smaller form factors and higher performance than current 2D designs, these advanced tests—already available in Synopsys’ TetraMAX ATPG product—become necessary for screening 3D systems.In addition, greater system complexity of 3D-ICs demands tighter control of dynamic power consumption, which differs pre-bond versus post-bond (since TSVs are used to distribute power up the stack in the latter case).

Advanced power management techniques, such as power-aware ATPG and power domain-based testing, are required to control power consumption and avoid false failures during 3D-IC testing. Power-aware ATPG generates patterns that limit both shift mode and capture mode power to functional levels based on a designer-specified power budget. Power domain-based test generates patterns in compliance with a design’s functional power states to reduce both dynamic and leakage power and avoid IR-drop issues. These advanced capabilities in the Synopsys test solution already have been successfully deployed to limit false failures on the tester, and will be essential for managing power during testing of 3D-ICs, which are also susceptible to increased thermal density and thermal variation [8].

Extensions to existing test automation that address very specific 3D-IC testing requirements include the ability to insert and connect TSV ports and related logic in a design, and the ability to generate “loopback” tests that allow data to be applied to and captured from the TSV I/Os to verify their functionality during KGD testing. For TSV connectivity tests, TetraMAX ATPG uses “dynamic bridging” fault models to generate at-speed patterns that can target time-sensitive shorts between TSV I/Os.

IV. PROPOSED TESTING SCHEME OF TSV ARRAYSScan Chain Method: Figure 3 shows the structure of a Scan Flip-Flop. The multiplexer is added at the input of the flip-flop to select between functional input D and Scan-In (SI). The selection between D and SI is governed by the Scan Enable (SE) signal. Series of n-scan flip-flops are connected in form

in, Scan-capture and Scan-out. Scan-in involves shifting in followed by loading all the flip-flops with an input vector. Once the sequence is loaded, one clock pulse (also called the capture pulse) is allowed to excite the combinatorial logic block and the output is captured at the second flop. The data is then shifted out and the signature is compared with the expected signature.Implementation of scan chain at 32nm node: A 1500-style die

of a chain, which effectively acts as a shift register. The first flop of the scan chain is connected to the scan-in port and the last flop is connected to the scan-out port.Scan operation involves three different operating stages: Scan-

Figure 3a. Scan Flip Flop.

Figure 3b. MOS Transistor based scan flop.

Figure 4a. CMOS Inverter Model.

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wrapper with scan-based TSV tests has been proposed for post-bond external tests [25]. We introduce a scan flop, as shown in Figure 3 that is to be used in the mentioned 1500-style die wrapper. As seen at the block level in Figure 3a, the gated scan flop accepts either a functional input or a test input from the scan chain; the selection is made depending on operational mode. In our design, shown at the transistor level in Figure 3c, two cross-coupled inverters are used to store data. Transmission gates are inserted between the cross-coupled inverters and at the input (D) and output (Q) of the flop itself.

Figure 4 shows a CMOS inverter with capacitive load C1. Figure 2 shows the output voltage Vout of CMOS inverter for a falling input Vin using CMOS 32 nm PTM model [19], [26]. t50 is the time for the gate output voltage from the initial point to 50% VDD.

The gate propagation delay tD is defined as the time interval from Vin = VDD/2 to Vout = VDD/2. From Figure 4b, gate delay can be represented as

tD= t50− tin / 2 (1)Figure 4(c) shows the delay time tDand the overshooting time

Figure 4c. Inverter response with various technologies [26].

Figure 4b. CMOS Inverter response for a falling input [26].

tov for various process technologies from 130 nm to 22 nm with typical supply voltages. The transistor length L is the minimum feature size. The widths of all PMOS transistors Wp are ten

Figure 5a. Simulated Inverter response.

Figure 5b. Inverter chain.

Figure 5c. Simulated response of inverter chain with 32 nm PTM model.

times of L while Wp is two times of Wn. The load capacitance C1 is 0.01 pF.

Results achieved by Zhangcai Huang e. al. [26] (shown in Figure 4b and Figure 4c) are verified by us on a SPICE tool using PTM 32 nm node technology. Figure 5a shows the CMOS inverter response for an input Vin with an approximate fall time of 100ps. The simulation results of the inverter achieved matches the results achieved in Figure 4c with an approximated error of 8% - 9%. These results are significant as scan flip flop shown in Figure 3b is implemented using the same CMOS inverter.

Currently, the use of delay models for performance cell based delay calculation has become an industry standard in practical .delay calculation tools. As cells are connected together by interconnect wires, the delay time of CMOS circuits between the input signal to output signal is just the sum of the delay time of each cell. To illustrate this, a chain of five inverters is used to observe the output waveform of each inverter as shown in Figure 5(b).

In Figure 5c., the delay time tD of the inverter chain is measured to be 21.4 ps.

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A REVIEW ON SUPERCAPACITORS

TSVs are connected to scan-flops, which are connected to form a scan chain [13]. Pre-bond testing of TSVs is difficult due to TSV pitch anddensity. Current probe technology using cantilever or vertical probes require a minimum pitch of 35μm, but TSVs have pitches of 4.4μm and spacings of 0.5μm. To address the aforementioned challenges, technique for pre-bond TSV testing that is compatible with current probe technology and leverages the on-die scan architecture that is used for post-bond testing. It utilizes many single probe needle tips, each to make contact with multiple TSVs, shorting them together to form a single network. This method requires probing, assuming that the die has already beenthinned and supported by a rigid platter (carrier) to prevent mechanical damage during probing.This method also allows for the concurrent testing of many TSVs to reduce overall test time.Furthermore, fewer probe needles are needed, which reduces the cost and complexity of probe equipment.

A method where all the scan-flops are initialized to known values is proposed. As shown in Figure 6a, scan flop 1 to 5 is initialized to logic HIGH or LOW. Multiple TSVs are shorted due to pitch limitations using current probe technology. We applied logic LOW or HIGH on the probe and read the values into the scan flop through the TSVs. A faulty TSV fails to update the new value into the scan flop and readily identified by shifting out the bit pattern.

Existing works deal with the post-bond test of TSVs by IEEE 1149.1 or IEEE 1500 test standards. Each TSV thus requires at least one register.

Figure 6(c) shows the simulation results achieved from the above scan chain. Clk frequency is taken at 5Ghz and scan signal is an input signal to the flop which puts the flop either in scan mode or conventional input mode. Scan flop selects multiplexed inputs (din) or serial data (sd) depending on the scan signal status (HIGH = scan mode, LOW = serial input mode). Open signal, determines whether the output Q floats or takes the value stored in the flip–flop.

IV. CONCLUSIONA cost-effective BIST scheme for testing TSVs of 3D ICs is presented in this paper. New on-chip measurement techniques targeted at 32nm ptm node technology that allows probing-based pre-bond testing of TSVs is introduced. Author demonstrated how these tests are applied to a network of TSVs, and presented LTSPICE simulation results to highlight the effectiveness of this approach.

V. REFERENCES[1]. John Baliga, “Chips go vertical,” IEEE Spectrum, March 2004.[2]. J. Joyner, R. Venkatesan, P. Zarkesh-Ha, J. Davis, and J. Meindl,

“Impact of three-dimensional architectures on interconnects in gigascale integration,” IEEE Trans. Very Large Scale Integr. (VLSI) Syst., Volume 9, No. 12, pp. 922–928, Dec. 2001.

Figure 6a. TSV network model.

Figure 6b. SPICE implementation of Scan chain.

Figure 6c. Simulation of scan chain at 32nm node.

Cascading scan flops to form scan chain:A TSV can be modeled as a wire with both a resistance and a capacitance. While a TSV may be manufactured from a number of different materials, copper is often used for metal layers and polysilicon may be a nonmetal alternative. The resistance of a TSV made from copper with a 2–5μm diameter and 5μm height is 80–200mΩ. For a polysilicon TSV with a 28–46μm diameter and 50μm height the resistance is 1.3–5.0Ω. The capacitance of a copper TSV with a 1–10μm diameter and 30–100μm height is 10–200fF. A probe needle makes contact with a number of TSVs at a time, as seen in Figure 6(a). The

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[3]. Nauman H. Khan, Syed M. Alam, and Soha Hassoun, “Power Delivery Design for 3-D ICs using Different Through-Silicon Via (TSV) Technologies,” IEEE Trans. Very Large Scale Integr. (VLSI) Syst., Volume 19, no. 4, April 2011

[4]. M. Bamal, S. List, M. Stucchi, A. Verhulst, M. Van Hove, R. Cartuyvels, G. Beyer, and K. Maex, “Performance comparison of interconnect technology and architecture options fordeep submicron technology nodes,” in Proc. Int. Interconnect Technol. Conf., 2006, pp. 202– 204.

[5]. J. W. Joyner, P. Zarkesh-Ha, J. A. Davis, and J. D. Meindl, “A three dimensional stochasticwire-length distribution for variable separation of strata,” in Proc. IEEE Int. Interconnect Technol. Conf., Jun. 2000, pp. 126–128.

[6]. D. H. Kim, S. Mukhopadhyay, and S. K. Lim, “Through-silicon-via aware interconnectprediction and optimization for 3D stacked ICs,” in Proc. ACM/IEEE Int. Workshop Syst.Level Interconnect Predict., Jul. 2009, pp. 85–92.

[7]. Dae Hyun Kim, Krit Athikulwongse, and Sung Kyu Lim, “Study of Through-Silicon-ViaImpact on the 3-D Stacked IC Layout,” IEEE Trans. Very Large Scale Integr. (VLSI) Syst., Volume 21, No. 5, May 2013.

[8]. T. Thorolfsson, K. Gonsalves, and P. D. Franzon, “Design automation for a 3D IC FFT processor for synthetic aperture radar: A case study,” in Proc. ACM Design Autom. Conf., Jul. 2009, pp. 51–56.

[9]. D. H. Kim and S. K. Lim, “Through-silicon-via-aware delay and power prediction model forbuffered interconnects in 3D ICs,” in Proc. ACM/IEEE Int. Workshop Syst. Level Interconnect Predict., Jun. 2010, pp. 25–32.

[10]. X. Dong and Y. Xie, “System-level cost analysis and design exploration for three-dimensional integrated circuits (3D ICs),” in Proc. Asia South Pacific Design Autom. Conf., Jan. 2009, pp. 234–241.

[11]. 3D ICs with TSVs – Design challenges and requirements, cadence, 2011.

[12]. Minki Cho, Chang Liu, Dae Hyun Kim, Sung Kyu Lim, and Saibal Mukhopadhyay, “Pre-Bond and Post-Bond Test and Signal Recovery Structure to Characterize and Repair TSVDefect Induced Signal Degradation in 3-D System,” IEEE Trans. On Components, Packingand Manufacturing Technology, Volume 1, no. 11, November 2011.

[13]. Krishnendu Chakrabarty, Brandon Noia, “Method and Architecture for Pre-bond Probing of TSVs in 3D Stacked ICs,”http://www.google.com/patents/US20130006557.

[14]. M. Cho, C. Liu, D. Kim, S. Lim, and S. Mukhopadhyay, “Design method and test structure to characterize and repair TSV defect induced signal degradation in 3D system,” in Proc. IEEE/ACM Int. Conf., Comput. Aided Design, Nov. 2010, pp. 694–697.

[15]. P.-Y. Chen, C.-W. Wu, and D.-M. Kwai, “On-chip testing of blind and open-sleeve TSVs for 3D IC before bonding,” in Proc. VLSI Test Symp., 2010, pp. 263–268.

[16]. D. Lewis and H.-H.S. Lee, “A scan island based design enabling prebond testability in die-stacked microprocessors,” in Proc. IEEE Int. Test Conf., Oct. 2007, pp. 1–8.

[17]. M. Beiley, J. Leung, and S. S. Wong, “A micromachined array probe card fabrication process,” IEEE Trans. Compon., Packag., Manuf. Technol, Volume 18, No. 1, pp. 179–183, Feb.1995.

[18]. B. Noia and K. Chakrabarty “Testing and design-for-testability techniques for 3D integrated circuits,” in Proc. 20th ATS, 2011, pp. 474–479.

[19]. http://ptm.asu.edu/ accessed on 11/06/2014[20]. Taouil, M., Hamdioui, S., Beenakker, K., Marinissen, E.J., “Test

Cost Analysis for 3D Die-to-Wafer Stacking,” 19th IEEE Asian Test Symposium (ATS), 2010, pp. 435–441.

[21]. Bottoms, W.R., “Test Challenges for 3D Integration (an invited paper for CICC 2011),” IEEE Custom Integrated Circuits Conference (CICC), 2011, pp. 1–8.

[22]. Marinissen, E.J., Daenen, T., Dupas, L., Van Dievel, M., Hanaway, P., Kiesewetter, J., Smith, K., Strid, E., Thärigen, T., “Wafer Probing on Fine-Pitch Micro Micro-Bumps for 2.5D- and 3D-SICs,” IEEE South-West Test Workshop–San Diego, California, June 2011.

[23]. Sayil, S., “Optical Contactless Probing: An All-Silicon, Fully Optical Approach,” IEEE Design & Test of Computers, Volume 23, Issue 2, 2006, pp. 138–146.

[24]. Zoschke, K., Wegner, M., Wilke, M., Jurgensen, N., Lopper, C., Kuna, I., Glaw, V., Roder, J., Wunsch, O., Wolf, M. J., Ehrmann, O., Reichl, H., “Evaluation of Thin Wafer Processing Using a Temporary Wafer Handling System as Key Technology for 3D System Integration,” 60th Proceedings of the Electronic Components and Technology Conference (ECTC), 2010, pp. 1385–1392.

[25]. E.J. Marinissen, J. Verbree, and M. Konijnenburg, “A structured and scalable test access architecture for TSV-based 3-D stacked ICs,” in Proc. IEEE VLSI Test Symp., 2010, pp. 269–274.

[26]. Zhangcai Huang, Atsushi Kurokawa, Masanori Hashimoto, Takashi Sato, Minglu Jiang, and Yasuaki Inoue, “Modeling the Overshooting Effect for CMOS Inverter Delay Analysis inNanometer Technologies”, IEEE Transactions on Computer-Aided Design of Integrated Circuits & Systems, Volume 29, No. 2, February 2010.

[27]. Yu-Jen Huang and Jin-Fu Li, “Built-In Self-Repair Scheme for the TSVs in 3-D ICs”, IEEE Transactions on Computer-Aided Design of Integrated Circuits & Systems, Volume 31, No. 10, October 2012.

Abdul Manan is working as an Assistant Professor in the department of Electronic and Electrical Engineering at G D Goenka World Institute - Lancaster University, Gurgaon. He has got 11 years of experience in the areas of teaching, research and industry. Mr. Manan obtained Bachelors degree in Engineering from Visveswaraya Technological University – Belgaum, Karnataka and M. Tech. degree from National Institute of Technology, Calicut, Kerala. Currently he is pursuing his

Doctorate from Jaypee University, Noida, Uttar Pradesh.

Abdul Manan has worked as RTL Design Engineer at Innovative Integration, California State, USA and Enventure Technologies, Bangalore, Karnataka. He has also worked on IP development and Memory Interfaces targeted to Field Programmable Gate Arrays in Real Time Applications. He is a life member of Indian Society of Technical Education (ISTE), New Delhi.

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Hybridisation of PTS-Clipping Techniques to Progress PAPR in MIMO-OFDM Systems

Raj Lakshmi Shukla1 and Monika Singh2

Department of Electronics Communication Engineering, National Institute of Technical Teachers Training and Research, Sector 26, Chandigarh 160019, [email protected], [email protected]

Abstract — The multiple input multiple output (MIMO) with orthogonal frequency division multiplexing (OFDM) is considered a promising solution to augment the channel capacity and multiplicity of wireless communication system without any enhancement in bandwidth. In this paper, an amalgam or hybrid combinational scheme is intended to reduce peak-to-average power ratio in MIMO–OFDM system under Rayleigh fading environment on an additive white Gaussian Noise channel. The proposed method intelligently fits in both clipping sequence and partial transmit sequence schemes. The results show that the proposed method not only reduces the PAPR but also maintains satisfactory bit error rate and computational complexity compared to other schemes.

Keywords: Clipping Techniques, MIMO OFDM, PAPR, AWGN.

I. INTRODUCTIONIN THE present scenario, 3G is not enough as the ever growing demands of multimedia services, online gaming etc. need higher speed of data. This can be achieved using 4G wireless technology. Multiple-input multiple-output (MIMO) with Orthogonal frequency division multiplexing (OFDM) is considered one of the promising solutions for increasing data rates in wireless communication systems. The main limitation of MIMO-OFDM system is its high peak-to-average power ratio (PAPR) of the transmitted signals which needs to be reduced. Antenna performance can be improved by applying a method known as MIMO and the caveat sign can be improved by the modulation technique of OFDM. This concept, as a whole, is known as MIMO-OFDM, and forms the basis of 4G technology.

OFDM is widely used technique due to its robustness and higher data rate transmission over frequency selective fading channel [1]. MIMO with OFDM is an alternative approach to achieve higher spectrum efficiency and data throughput for broadband wireless communication system without any expansion in the bandwidth [2, 3]. To further improve the overall system performance over channels with large delay spread, the space time block coding (STBC) technique [4] is also applied in MIMO–OFDM. Though, the MIMO–OFDM [5–7] offers multitudinous benefits, when large peak signals enter amplifier

saturation region, deformation occurs. This increases PAPR of the system and reduces its recital and performance in terms of bit-error rate (BER).

In literature, various conventional [8–11] and hybrid [12–16] techniques were proposed for reducing the PAPR of MIMO–OFDM system. Each straight scheme possesses its own merits and demerits in terms of the out-of-band interference, and data rate loss. Though, the hybrid method combines a couple of conventional schemes together and accumulates their remuneration and benefits in a combinational approach, but the computational complexity in combinational method is also a major issue of apprehension. Therefore, in this paper, a parallel combination of clipping and partial transmit sequence (PTS) schemes are prudentially applied to augment the performance of MIMO–OFDM system. The proposed method not only reduces the PAPR of MIMO–OFDM signals but also maintains the data rate and provides low in-band ripples and out-of-band radiations. Moreover, the proposed scheme also offers less computational complexity compared to an alike combinational scheme.

OFDM is today a widespread technique for broadcast and transmission of signals over wireless channels and adopted in many wireless standards. OFDM may be united with antenna arrays at the transmitter and receiver side to improve the diversity gain and to improve the system competence on time-

Figure 1. Block diagram of MIMO-OFDM system.

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variant frequency-selective channels, resulting in a multiple-input multiple-output composition.

II. MIMO-OFDM ORGANIZATIONMultiple Input Multiple Output Orthogonal Frequency division multiplexing is a technique that uses multiple antennas to send and get back radio signals. The block diagram of desired scheme for MIMO–OFDM system is shown in Figure 1 which has N number of antennas at transmitter and receiver side.

OFDM can transform a frequency-selective MIMO channel into a set of parallel frequency-flat MIMO channels and thus increase the frequency efficiency. Therefore, MIMO-OFDM technology was researched as the infrastructure for next generation wireless networks. MIMO wireless systems, combined with OFDM, allowed for easy transmission of symbols in time, space and frequency. MIMO-OFDM takes advantage of the multipath properties of environments [17] using base station antennas that do not have LOS and uses both the advantages of MIMO and OFDM.

Combination of MIMO and OFDM techniques will impact the evolution of wireless LANs, and is a leading contender for fourth generation (4G) wireless communications systems. Therefore, MIMO-OFDM [18] system is a welcome proposal for 4G mobile communication systems. Advantage is very high competence, spectral efficiency and improved communications reliability i.e., reduced bit error rate (BER) [19] achieved at reasonable computational complexity.

III. SYSTEM MODELConsidering MIMO OFDM system with a configuration in which the input data stream is the mapped into N number of orthogonal symbols. The space time block coding [20] is used to improve the overall performance of MIMO–OFDM system.

The time domain signal xi(n) is obtained by IFFT operations

transmitted signal exceeding a given PAPR threshold λ and is given by

CCDF=1−PrPAPR≤ λ=1−(1−eλ)N (3)

IV. SELECTION OF PAPR REDUCTION SCHEMESIn general, the PAPR reduction schemes are broadly classified into four main categories:

Signal distortion: The PAPR reduction is possible by distorting the OFDM signal non-linearly in time domain. The clipping and filtering technique, peak windowing and non-linear companding are a few methods of this kind. Performance of clipping scheme is easy, but its BER presentation degrades due to in-band signal distortion [21]. The Non-linear Companding mainly focuses on enlarging small amplitude signals whilst keeping peak signals unchanged, and so it increase the average power of the transmitted signals and possibly results in degradation of the BER performance with the increase in value of μ.

Coding methods: The concept behind the coding schemes is to lessen and cut the occurrence probability of the same phase of N signals [22]. The coding method reduces the PAPR, but it suffers from bandwidth efficiency, in particular for a large number of sub-carriers.

Scrambling techniques: The Selective Mapping (SLM) and Partial Transmit Sequence (PTS) are two proven schemes of this category which partitions different scrambling sequences and selecting that sequence which gives smallest PAPR.. The major drawbacks of these schemes are computational complexity and requirement of side-information to recover original data block at the receiver side.

Pre-distortion method: These methods are based on the re-orientation or spreading the vigour and energy of data symbol, which include DFT spreading, pulse shaping or pre-coding and constellation shaping schemes. The Tone Reservation (TR), Active Constellation Extension (ACE), and Tone Injection (TI) are two fit techniques for PAPR reduction which are based on the reorientation (shaping) of constellation. The Active Constellation Extension (ACE) practice is used to obtain good performance including PAPR reduction and low complexity [23]. The main advantage of ACE is that it does not require any side information to recover original sequence.

The hybrid/combinational methods seem to be a better choice for PAPR reduction because it possesses the merits of both techniques used in combination. Therefore, in this paper, a hybrid schemes based on clipping and partial transmit sequence (PTS) is taken. In this section, the proposed hybrid PAPR reduction technique which has been obtained by the alliance of PTS method with clipping method is presented. One performs linear conversion or transformation by rotating the vectors from

where i=1,...,NT and n=0,1,…,LN−1. L is the oversampling factor. PAPR can be defined as the relationship between the maximum power of a sample in a transmit OFDM symbol and its average power, and it is written as,

(1)

(2)

where E[.] symbolizes the expectation. The PAPR performance is portrayed by using complementary cumulative distribution function (CCDF), which is defined as the chance of the

9

HYBRIDISATION OF PTS-CLIPPING TECHNIQUES

the frequency-domain signal, and the other one performs a non-linear alteration represented by signal limitation. The block diagram of the put forwarded method is presented in Figure 2.

The presentation and recital of the proposed PAPR diminution or reduction technique is hereby analyzed with a MATLAB simulator as presented in Figure 3.

Within this simulator, the samples from the generated signal are mapped from binary representation to the M-QAM constellation points. The obtained complex values are grouped in blocks of N elements each, forming the MIMO-OFDM symbols. Similar to [24] we consider a generic MIMO-OFDM/A downlink scenario with one base station (BS) employing antennas. An OFDM block with subcarriers is transmitted from each antenna. The subcarriers comprises of useful subcarriers surrounded by two guard bands with zero energy. The useful subcarriers are thronged into resource blocks (RBs) each consisting of subcarriers. Data of one or many users is placed in these RBs and mapped into the space-time domain using an inverse discrete Fourier transform (IDFT) and space-time block coding (STBC). To allow channel inference at the receivers (mobile

stations), each RB also contains several pilot subcarriers that act as training symbols. The transmit signal model which shows the data structure of an OFDM block for a MIMO-OFDM/A is shown in figure 4.

The obtained MIMO-OFDM frames are applied sequentially to PTS block and then to clipping block. The PTS method operates on the frequency-domain signal iteratively until the best signal derivate is actually found. The main idea of this approach is to alter the phases of the vectors composing the signal. This method considers the signal’s vectors as being grouped in disjoint blocks. The vectors from a block may have a nearby displacement, or they may be interleaved with the vectors representing another block. The algorithm applies one phase shift for each block iteratively until the signal variant having the lowest PAPR is found. In the present work, the PTS method was implemented considering contiguous or nearby blocks of same length each. To add on, for a better PAPR reduction, the proposed PTS method performs position swap between these blocks.

V. PARTIAL TRANSMIT SEQUENCE (PTS) It is one of the most wanted techniques for PAPR reduction in OFDM. Here the input frequency domain data block is first partitioned into disjoint sub-blocks. Then each of the sub-blocks are then padded with zeros appropriately and weighted by complex phase factors. The data vector X=[xo,x1,x2....xN-1]T is divided in V disjoint sets, Xv, v = 1,2..V , using same number of carrier for each group.

X’ = ∑Xv bv v= 1 to V, (4)

where bv = are the phase factors. Select one suitable factor amalgamation 𝐛 = [𝑏1,2,…,𝑏𝑣] which makes the result achieve optimum. At receiver to recuperate the signal, some side information about phase weighting sequences is required; this side information needs log2 W

V bits to be transmitted separately.

VI. CLIPPING AND FILTERINGThis is simplest technique used for PAPR reduction of OFDM signal. A Clip is also called as non linear saturation which is employed about the peaks to reduce the peaks before high power amplifier to lessen PAPR and so is called Clipping

Figure 2. Hybrid PTS-Clipping Scheme.

Figure 3. Proposed Sculpt for the analysis of hybrid PAPR reduc-tion technique and BER improvement.

Figure 4. Structure of data of an OFDM block for MIMO system.

10


Technique. This is simple technique but it commences Out Of Band Radiation and In Band Distortion in OFDM Signal. Joint filtering and clipping technique reduce the OOB radiation but IB distortion are still there since this method degrades OFDM system performance e.g. spectral efficiency and BER. Envelop scaling is used for PAPR reduction due to equality envelop properties of all subcarriers input [25] Clipping means the amplitude of the signal is clipped at the predefined values which limit the peak value of the input signal to a predetermined value.

Let Y[n] denote the input signal and Yc [n] denote the clipped signal of Y[n], which can be represented as, where B is the threshold or predetermines value of clipping level. Clipping is simple but yet it has some drawback. Clipping cause signal distortion which increase bit-error-rate

Figure 5. PTS Block Diagram.

(6)

performance. After filtering operation performed on the clipped signal, the clipping level may exceed the signal specified for the clipping operation.

VII. RESULTSThe PAPR calculation have been done for N= 256 and 512 FFT size having CR ratio as 12. The blue coloured graph is the CCDF for the original signal. Once PTS technique in accordance with the block diagram is applied to the original signal then, PAPR is further reduced. Now to the signal which comes after PTS block based upon the phase and block indices is sent for the clipping which actually clips the signal based upon some defined threshold value and this is the actual hybrid signal which can be seen from a cross sectional area in Figure 8 and 9. PAPR is reduced by approximately 1.7 dB which can be deduced from Figure 6 and 7 and table 1. BER performance is calculated over Rayleigh fading channel of MIMO-OFDM with AWGN which actually shows that BER performance improves as number of subcarriers decreases that is BER is better for size 256 as to 512 which can be seen from figure 8 and 9 and can be interpreted from Table 2.

Figure 6. PAPR for FFT size-256.

Figure 7. PAPR for FFT size 512.

Figure 8. BER for FFT Size 256 in Rayleigh Fading Environment.

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HYBRIDISATION OF PTS-CLIPPING TECHNIQUES

VIII. CONCLUSIONThough all the techniques in individual and hybrid effects gives good results but still every method is having certain shortcomings. Here in this paper the hybrid PTS and clipping techniques have been implemented on MIMO-OFDM system with the number of subcarriers as 256 and 512. The significant difference is a reduction in PAPR value and also the improvement in BER is noticed which decreases as the SNR value increases.

IX. ACKNOWLEDGEMENTAuthors thank Dr. M.P. Puniya, Director NITTTR, Chandigarh, Dr. Maitrayee Dutta, HOD-ECE, NITTTR, without whose support and valuable guidance things would not have been practically implemented. Last, we thank our colleagues for giving their endless support.

X. REFERENCES[1]. Soo, Y., Kim, J., Yang, W. Y. and Kang,C.G “MIMO–OFDM

Wireless Communications with Matlab”, 2010.[2]. Peppas, K., Lazarakis, F., Axiotis, D. I., Al-Gizawi, T. and

Alexandridis, A. A. “System level performance evaluation of MIMO and SISO OFDM-based WLANs”. Wireless Networks. Volume 15, Issue 7, pp. 859-873 2009

[3]. Urosevic, U., Veljovic, Z., & Pejanovic-Djurisic, M., “MIMO solution for performance improvements of OFDMCDMA system with pilot tone”. ibid., Volume 19, Issue 8, pp. 2021-2028, 2013.

[4]. Alamouti, S. M.,“A simple transmit diversity technique for wireless communication”. IEEE Journal on Selected Areas in Communications,Volume 16, pp. 1451–1458, 1998.

[5]. Kwon, U., Kim, D., Kim, K., and Im, G., “Amplitude clipping and iterative reconstruction of STBC/SFBC–OFDM signals”. IEEE Signal Processing Letters, Volume 14, Issue 11, pp. 808–811, 2007.

[6]. Li, Z. and Xia, X., “Single-symbol ML decoding for orthogonal and quasi-orthogaonal STBC in clipped MIMO–OFDM systems using a clipping noise model with Gaussian approximation”. IEEE Trans. Communications, Volume 56, Issue 7, pp. 1127–1136, 2008

[7]. Zhu, Xiaodong, “A low-BER clipping scheme for PAPR reduction in STBC MIMO–OFDM systems”. Wireless Personal Communications. Volume 65, Issue 2, pp 335-346, July 2012.

[8]. Bäuml, R. W., Fischer, R. F. H. and Huber, J. B. “Reducing the peak-to-average power ratio of multicarrier modulation by selected mapping”. IEEE Electronics Letters, Volume 32, Issue 22, pp. 2056–2057, 1996.

[9]. Müller, S. H. and Huber, J. B., “OFDM with reduced peak-to-average power ratio by optimum combination of partial transmit sequences”.IEEE Communications Letters, Volume 33,Issue 5, pp-368–369, 1997.

[10]. Krongold, B. S. and Jones, D. L., “PAR reduction in OFDM via active constellation extension”. IEEE Trans. Broadcasting, Volume 49, Issue 3, pp. 258–268, 2003.

[11]. Mishra, A., Saxena, R. and Patidar, M. AGP–NCS scheme for PAPR reduction. Wireless Personal Communications. Volume 82, Issue 3, pp. 1201-1212, June 2015.

[12]. Mishra, A., Saxena, R. And Patidar, M,. “OFDM link with a better performance using artificial neural network”. Wireless Personal Communications, Volume 77, pp.1477-1487, July 2014.

[13]. Ghassemi, A. and Gulliver, T. A. “PAPR Reduction of OFDM using PTS and error-correcting code sub-blocking”. IEEE Trans. Wireless Communication, Volume 9, Issue 3, pp. 980–989.

[14]. Lee, B. M., Kim, Y. And de Figueiredo, R. J. P. “Performance analysis of the clipping scheme with SLM technique for PAPR reduction of OFDM signals in fading channels”. Wireless Personal Communication, Volume 63, issue 2, pp. 331–344, 2012.

[15]. Duanmu, C. And Chen, H. 4), “Reduction of the PAPR in OFDM systems by intelligently applying both PTS and SLM Algorithms”, Wireless Personal Communication, Volume 74, Issue 2, pp. 849-863, 2014

[16]. Pachori, K. And Mishra, A., “PAPR Reduction in MIMO–OFDM by using active partial sequence”. IEEE Trans. Circuits, Systems and Signal Processing, 2015

Figure 9. BER for FFT size 512 in Rayleigh Fading Environment.

TABLE 1 COMPARISON OF PAPR VALUES FOR HYBRID, PTS AND

ORIGINAL PAPR SIGNAL FOR DIFFERENT FFT SIZESFFT SIZE Hybrid

(PAPR dB)PTS(PAPR dB) Original

PAPR(dB)256 9.6 9.8 11.3512 10.1 10.1 11.8

TABLE 2 COMPARISON OF BER VS. SNR FOR HYBRID, PTS AND ORIGINAL PAPR FOR DIFFERENT FFT SIZE

FFT Size

Hybrid 5 dB

Hybrid 10 dB

PTS 5 dB

PTS10 dB

Original 5 dB

Original 10 dB

256 .015 .0015 .017 .0019 .018 .0022

512 .038 .004 .042 .0048 .049 .0052

12


[17]. Hasegawa, T. and Shimizu, M., “Multipath interference reduction property by using multipath interference correlative timing throughout for DS-CDMA systems,” The 57th IEEE Semiannual Vehicular Technology Conference, 2003. VTC 2003-Spring., Volume 4, pp.2827-2831, 2003.

[18]. Oborina, Alexandra; Moisio, Martti and Koivunen, Visa, “Performance of Mobile MIMO OFDM Systems With Application to UTRAN LTE Downlink,” IEEE Transactions on Wireless Communications, Volume 11, no.8, pp.2696-2706, 2012.

[19]. Hasna, M.O., “Average BER of multihop communication systems over fading channels,” 10th IEEE International Conference on Electronics, Circuits and Systems, 2003, Volume 2, pp.723-726 , 2003.

[20]. Ochiai, H. and Imai, H.. Performance analysis of deliberately clipped OFDM signals. IEEE Trans. Communications, Volume 50, Issue 1, pp. 89–101, 2002.

[21]. Li, X. and Cimini, L. J., Jr. Effects of clipping and filtering on the performance of OFDM. IEEE Communications Letters, Volume 2, Issue 5, pp. 131–133, 1998.

[22]. Wulich, D.). Reduction of peak to mean ratio of multicarrier modulation using cyclic coding. IEEE Electronics Letters, Volume 32, No. 29, pp. 432–433, 1996.

[23]. Han, S. H., Cioffi, J. M. and Lee, J. H.). On the use of hexagonal constellation for peak-to-average power ratio reduction of an OFDM signal. IEEE Trans Wireless Communication, Volume7, Issue3, pp. 781–786, 2008.

[24]. S. Khademi, A.-J. van der Veen and T. Svantesson, “Precoding technique for peak-to-average-power-ratio (PAPR) reduction in

MIMO OFDM/A systems,” in , 2012 IEEE Int. Conf. Acoustics, Speech and Signal Processing (ICASSP), pp. 3005–3008, 2012.

[25]. T. Wattanasuwakull and W. Benjapolakul, “PAPR Reduction for OFDM Transmission by using a method of Tone Reservation and Tone Injection”, IEEE Trans. ICSC, pp. 273-277, 2005.

Raj Lakshmi Shukla received the B.Tech. degree in electronics and communication engineering from Krishna Institute of Engineering and Technology, Muradnagar, Uttar Pradesh Technical University, India, in 2004. Obtained M.E. in electronics and communication engineering (Communication Systems) from Panjab University NITTTR, Chandigarh, India in 2015. She has abiding passion for teaching, with over 8 years of experience, primarily at VIET. Presented and published 6

articles. Her research interests include Communication networks, wireless communication, neural networks and fuzzy logic. She is presently with IEC, Greater Noida.

Monika Singh is M.E. scholar from Institute of Technical Teachers Training and Research, Chandigarh India. She is having five years of teaching experience. She has completed her B.Tech from Babu Banarsi Das Institute of Engineering Technology And Research Center from Uttar Pradesh in 2009. Her interest areas are Digital Signal Processing, VLSI Design, Digital Electronics, and Wireless Communication. She is presently with N.I.E.T., Greater Noida.

13

Electricity Generation Due to Vibration by BootsVaibhav Sharma1 and Mohini Preetam Singh2

Vidya College of Engineering, Vidya Knowledge Park, Baghpat Road, Meerut 250002 UP [email protected], [email protected]

Abstract — Mechanical energy that is generated by relative movement on the road is converted into electric energy by piezoelectric effect. Piezoelectricity is the electric charge that accumulates in certain solid material (notably crystal, certain ceramic and biological matter such as bone, DNA and various proteins) in response to applied mechanical stress. The aim of this research work is to make power generation more sustainable, economic and ecological by utilizing the advancement in technology.

Keywords: Mechanical energy, piezoelectric effect, Sustainable power.

I. INTRODUCTIONAS piezo-energy harvesting has been investigated only since the late 1990s [1], it remains an emerging technology. When people walk or run, the piezoelectric materials under the boots vibrate and produce electricity in large amount [2]. Piezoelectricity is the electric charge that accumulates in certain solid materials (such as crystals, certain ceramics, and biological matter such as bone, DNA and various Proteins) [3] in response to applied mechanical stress.

Piezoelectricity was discovered in 1880 by French physicists Jacques and Pierre Curie [4]. The piezoelectric effect is understood as the linear electromechanical interaction between the mechanical and the electrical state in crystalline materials with no inversion symmetry [5]. The piezoelectric effect is a reversible process in that materials exhibiting the direct piezoelectric effect (the internal generation of electrical charge resulting from an applied mechanical force) also exhibit the reverse piezoelectric effect (the internal generation of a mechanical strain resulting from an applied electrical field) [6-9].

For example, lead zirconate titanate crystals will generate measurable piezoelectricity when their static structure is deformed by about 0.1% of the original dimension. Conversely, those same crystals will change about 0.1% of their static dimension when an external electric field is applied to the material. The inverse piezoelectric effect is used in production of ultrasonic sound waves [6, 8, 10].

Piezoelectricity is found in useful applications such as the production and detection of sound, generation of high voltages, electronic frequency generation, microbalances, and ultrafine

focusing of optical assemblies. It is also the basis of a number of scientific instrumental techniques with atomic resolution, the scanning probe microscopies. Most piezoelectric electricity sources produce power [11-12] on the order of milli watts, too small for system application, but enough for hand-held devices such as some commercially available self-winding wrist watches. One proposal is that they are used for micro-scale devices, such as in a device harvesting micro-hydraulic energy. This paper is put up to provide the base for further improvements and considering the fact that failures faced in our work will guide future [15].

II. MECHANISM FOR PIEZOELECTRICITYMany materials, both natural and synthetic, exhibit piezoelectricity. Crystals which acquire a charge when compressed, twisted or distorted are said to be piezoelectric. This provides a convenient transducer effect between electrical and mechanical oscillations: The generation of an electric charge in certain non conducting materials, such as quartz crystals and ceramics, when they are subjected to mechanical stress (such as pressure or vibration), or the generation of vibrations in such materials when they are subjected to an electric field.

Piezoelectric materials exposed to a fairly constant electric field tend to vibrate at a precise frequency with very little variation. The nature of the piezoelectric effect is closely related to the occurrence of electric dipole moments in solids. Of decisive importance for the piezoelectric effect is the change of polarization P when applying a mechanical stress. This might either be caused by a re-configuration of the dipole-inducing surrounding or by re-orientation of molecular dipole moments under the influence of the external stress.

Piezoelectricity may then manifest in a variation of the polarization strength, its direction or both, with the details depending on (i) the orientation of P within the crystal, (ii) crystal symmetry and (iii) the applied mechanical stress. The change in P appears as a variation of surface charge density upon the crystal faces, i.e. as a variation of the electrical field extending between the faces caused by a change in dipole density in the bulk. For example, a 1 cm3 cube of quartz with 2 kN of correctly applied force can produce a voltage of 12500 V [13]. There is a magnetic analog where ferromagnetic

14


material responds mechanically to magnetic fields. This effect, called magnetostriction, is responsible for the familiar hum of transformers and other AC devices containing iron cores.

Piezoelectric materials also show the opposite effect, called converse piezoelectric effect, where the application of an electrical field creates mechanical deformation in the crystal. Piezoelectric materials exhibit both a direct and a reverse piezoelectric effect. Figure 1 indicates conversion of vibration/ mechanical energy into electrical energy and vice versa. The direct effect produces an electrical charge when a mechanical vibration or shock is applied to the material, while the reverse effect creates a mechanical vibration or shock when electricity is applied. Any spatially separated charge will result in an electric field, and therefore an electric potential. In a piezoelectric device, mechanical stress, instead of an externally applied voltage, causes the charge separation in the individual atoms of the material. Figure 2 indicates generation of piezoelectricity for polar crystals, for which P ≠ 0 holds without applying a mechanical load, the piezoelectric effect manifests itself by changing the magnitude or the direction of P or both. For the non-polar, but piezoelectric crystals, on the other hand, a polarization P different from zero is only elicited by applying a mechanical load. For them the stress can be imagined to transform the material from anon-polar crystal

class (P =0) to a polar one [14], having P ≠ 0. Figure 3 shows mechanism of piezoelectric effect in quartz.

III. SOURCES OF VIBRATIONS FOR CRYSTALPower Generating Boots or Shoes: In United States Defense Advance Research Project Agency (DARPA) initiated an innovative project on Energy harvesting which attempts to power battlefield equipment by piezoelectric generators.

Embedded in soldiers’ boots. However, these energy harvesting sources put an impact on the body. DARPA’s effort to harness 1-2 watts from continuous shoe impact while walking was abandoned due to the discomfort from the additional energy expended by a person wearing the shoes.

Power Generating Sidewalk: The piezoelectric crystal arrays are laid underneath pavements, side walks and other high traffic areas like highways, speed breakers for maximum voltage generation. The voltage thus generated from the array can be used to charge the chargeable Lithium batteries, capacitors etc. These batteries can be used as per the requirement.

Gyms and Workplaces: Researchers are also working on the idea of utilizing the vibrations caused from the machines in the gym. At workplaces, while sitting on the chair, energy can be stored in the batteries by laying piezoelectric crystals in the chair. Also, the studies are being carried out to utilize the vibrations in a vehicle, like at clutches, gears, seats, shock-ups, foot rests.

Mobile Keypad and Keyboards: The piezoelectric crystals can be laid down under the keys of a mobile unit and keyboards.

Figure 1. Conversion of Mechanical Energy into Electric Energy and vice-versa.

Figure 2. Mechanism of piezoelectric effect in quartz crystal.

Figure 3. Principle of direct piezoelectric effect.

Figure 4. Single-Piezo Transducer.

15

With the press of every key, the vibrations created can be used for piezoelectric crystal and hence can be used for charging purpose.

Floor Mats, Tiles and Carpets: A series of crystals can be laid below the floor mats, tiles and carpets which are frequently used at public places.

People Powered Dance Clubs: In Europe, certain nightclubs have already begun to power their night clubs, strobes and stereos by use of piezoelectric crystals. The crystals are laid underneath the dance floor. When a bulk of people use this dance floor, enormous amount of voltage is generated which can be used to power the equipments of the night club.

IV. BUILDING SETUPInitiation was started up by reading the concept of Piezo electricity. Then, after searching for the component (Piezo Transducer) required making the phenomena work, the working and connections were learned practically by using soldering, connecting wires and multimeter etc. Then, Searching internet and thinking led us to its various applications that could act

as a free energy and a potential sustainable energy for future. For making the ‘Walk N Charge Boot’ the arrangement uses three sets connected in series of two parallel connected Barium Titanate piezoelectric transducers. Figure 4 shows sample of transducer used in experiment. Since these transducers produce Alternating Current, it needed to be converted to dc by using a bridge rectifier as shown in Figure 5 and gives 5V-15V as output. The output of bridge rectifier is connected to the charging wire of the power bank of 200mAH as shown in Figure 6.

Further it was experimented that this shoe while used in jogging will charge the 200 mAH power bank in 6 hours for 1 shoe out of a pair. These small piezo transducers could also arranged from buzzers used in scooter indicators, etc. Thus, almost all the material used in setup is almost free and could be arranged at inexpensive rates. Moreover, the discomfort caused with this setup in the shoes is just the elevated heel by half to one an inch.

V. COST EFECTIVENESSThe assembly developed using series and parallel combination of piezo-crystals is very cost effective. A single crystal costs around 23 – 25 Rupees when purchased in bulk of 10, and hence the cost of whole assembly including wires, base of setup, hard cardboard etc. is very less. It’s just that u need a power bank to store the energy generated, and it will cost around 150 Rupees for 200 mAH. It is very encouraging to get a good voltage and current at such a low cost at the same time utilizing the waste energy. So, the assembly improves on the concern of cost effectiveness to a great extent and we are working on it to further improve upon the results of the system.

VI. FUTURE SCOPEThe proposed work portrays the concept of Piezoelectric Energy Harvesting and the results obtained after the implementation are very encouraging. Future work of the proposed idea encompasses further amplification of the crystal output to a greater extent. Future lies in the inclusion of advanced material used to design the piezoelectric crystal which further amplifies the crystal output in terms of voltage as well as current. A study could be carried out from the variety of piezoelectric crystals and after comparing the results, the choice of the optimum material for the best performing crystal could be devised. Further, amplifying the output by using the Operational Amplifier could improve the Efficiency.

VII. CONCLUSIONThe amount of energy generated depends on the number of Steps taken during walking, intensity of footsteps and the pile of piezoelectric Transducers in the boot. Jogging and running produce slight more energy than via walking, but further research is needed to confirm this piezoelectric power generation system works successfully. It has tremendous scope for future energy/ power solution towards sustainability.

Figure 5. Demonstration Setup.

Figure 6. Complete Built-in Arrangement.

ELECTRICITY GENERATION DUE TO VIBRATION BY BOOTS

16


VIII. REFERENCES[1]. White, N.M., Glynne-Jones, P. and Beeby, S.P. ‘A novel

thick-film piezoelectric micro-generator’, Smart Materials and Structures, Volume 10, No. 4, pp. 850-852, 2001.

[2]. Abbasi, Aqsa. “Application of Piezoelectric Materials and Piezoelectric Network for Smart Roads.” International Journal of Electrical and Computer Engineering , Volume 3, No.6 , pp. 857-862, 2013.

[3]. Holler, F. James; Skoog, Douglas A; Crouch and Stanley R (2007). “Chapter 1”. Principles of Instrumental Analysis (6th ed.). Cengage Learning. p. 9. ISBN 978-0-495-01201-6.

[4]. Manbachi, A. and Cobbold R.S.C. “Development and Application of Piezoelectric Materials for Ultrasound Generation and Detection”. Ultrasound, Volume 19, No. 4 , pp. 187–196, 2001.

[5]. Gautschi, G. Piezoelectric Sensorics: Force, Strain, Pressure, Acceleration and Acoustic Emission Sensors, Materials and Amplifiers. Springer, 2002.

[6]. Katzir, S. (2012-06-20). “Who knew piezoelectricity? Rutherford and Langevin on Submarine Detection And The Invention of Sonar”. Notes Rec. R. Soc. 66 (2): pp. 141–157.

[7]. S. Trolier-McKinstry. “Chapter3: Crystal Chemistry of Piezoelectric Materials”. In A. Safari, E.K. Akdo˘gan. Piezoelectric and Acoustic Materials for Transducer Applications. New York: Springer. ISBN 978-0-387-76538-9, 2008.

[8]. Kochervinskii, V. “Piezoelectricity in Crystallizing Ferroelectric Polymers”. Crystallography Reports, 48 (4): 649–675, 2003.

[9]. Fotiadis, D.I; Foutsitzi, G., and Massalas, C.V (1999). “Wave Propagation Modeling in Human Long Bones”. ActaMechanica, 137: pp. 65–81.

[10]. Lee, BY; Zhang, J; Zueger, C; Chung, WJ; Yoo, SY; Wang, E; Meyer, J; Ramesh, R and Lee, SW. “Virus-Based Piezoelectric Energy Generation,” Nature nanotechnology, Volume 7, No. 6, pp. 351–356, 2012.

[11]. Gurdal, Erkan A.; Ural, Seyit O.; Park, Hwi-Yeol; Nahm, Sahn; Uchino, Kenji. “High Power (Na0.5K0.5) NbO3-Based Lead-Free Piezoelectric Transformer”. Japanese Journal of Applied Physics, Volume 50, No. 2, 027-101, 2011.

[12]. Website/ URL at www.merriam-webster.com[13]. Sensor Sense: Piezoelectric Force Sensors, at www.

Machinedesign.com[14]. M. Birkholz (1995). “Crystal-field induced dipoles in

heteropolar crystals – II. Physical significance”. Z. Phys. B , Volume 96, No. 3, pp. 333–340.

[15]. ‘Stop writers from writing; in the span, needs to be hidden from future’. — Mrs. Om Lata Singh.

Mohini Preetam Singh received Bachelor’s degree in Electronics and Instrumentation from UPTU, India and Master’s degree in Microelectronics from Subharti University, India. She received Academic Excellence award for research work in “NEGF Approach in Silicon Nanowire Transistors” in her Master’s. She is working as an Assistant Professor in Vidya College of Engineering since 2010. Her current work focus is on “Low power consumption techniques for embedded systems”.

Vaibhav Sharma is pursuing his Bachelor’s degree in Computer Science and Engineering from UPTU, India. Presently he is working on web and android based projects, along with soft computing, algorithms, networking, data compression etc.

17

Kinematic Modeling of a Multi-Fingered Robotic Hand - a Review

M. Z. Hussain1 and Dr. M. Suhaib2

Department of Mechanical Engineering, Jamia Millia Islamia, New Delhi, 110025 [email protected], [email protected]

Abstract — This paper presents a survey of work in kinematic and dynamic modeling and analysis of multi-fingered robotic hand over the last several years. It provides an insight towards the development of theoretical framework.

Keywords: Kinematics, Dynamics, Modeling, Multi-Fingered Hand, Grippers and Jacobian.

I. INTRODUCTIONA ROBOT is an automatic mechanical device often resembling a human or animal. Modern robots are usually electro-mechanical machines guided by a computer program or electronic circuitry. Robots can be autonomous or semi-autonomous and range from humanoids to industrial robots, collectively programmed swarm robots, and even microscopic and nano robots. Robotic hand is the end effector, or robotic hand, can be designed to perform any desired task such as welding, gripping, spinning etc., depending on the application. Robotic hands are classified as two fingered robotic hand and multi-fingered robotic hand (MFRH).

The multi-fingered robot hand has already been designed and fabricated to accommodate a variety of tasks such as grasping and manipulation of objects in the field of industrial

applications. The first step in realising a fully functional multi-fingered robot hand is mathematical modeling. A multi fingered robotic hand model is studied based on the biological equivalent of human hand.

II. LITERATURE REVIEWJ. Denavit and R.S. Hartenberg [1] described any robot kinematically by giving the values of four quantities for each link. Two describe the link itself, and two describe the link‘s connection to a neighboring link. In the usual case of a revolute joint, is called the joint variable, and the other three quantities would be fixed link parameters. For prismatic joints, di is the joint variable, and the other three quantities are fixed link parameters. The definition of mechanisms by means of these quantities is a convention usually called the Denavit-Hartenberg notation.

John J. Craig. [2] presented a technique for convention and notation which can be used to develop the kinematics and dynamics equation. Victor J. Johnson and Gregory P. Starr [3] develop the kinematic and dynamic equations for one finger of the three-fingered Stanford/JPL robot hand and document the physical parameters needed to implement the equations. The equations can be used in control schemes for position and force control of the Stanford/JPL robot hand. S. Parasuraman, and Ler Shiaw Pei [4] carry out the bio-mechanical analysis of human joints and the study is extended to the robot manipulator. The paper focused on the kinematics of human arm which include the movement of each joint in shoulder, wrist, elbow and finger complexes. Those analyses are then extended to the design of a human robot manipulator.

Valentin Grecu et al. [5] articulate that the finger consists of a set of rigid segments connected with joints. Each finger joint angle will be computed by the given fingertip position and orientation. Izzeldin Ibrahim Mohamed Abdelaziz [6] focus on the design of compact five fingers real time smart glove to emulate the human hand functions that can be used as a prototype model for hand rehabilitation systems for patients suffering from paralyze or contracture. This work tried to emulate the grip function and develop a prototype model. Kosuge and Furuta [7] presented a quantitative measure of controllability of robot arms. This measure is representative of Figure 1. Model of MFRH.

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the input-output relation of a robot arm at a point, and related to both kinematic and dynamic properties of the arm including actuators. The analysis presented in this paper is efficient for the design of an arm and also seems to be useful for control problems such as the optimum path planning, the singularity and obstacle avoidance. Wan Faizura Binti Wan Tarmizi, et al. [8], gave the complete derivation of the mathematical modeling comprising the kinematics and dynamic of multi fingered robotic hand which was carried out using Denavit Hartenburg (DH) algorithm[1] and Euler Langrange formula [2] to enable subsequent simulation work.

In this paper, a robotic hand model is proposed based on the biological equivalent of human hand where each links interconnect at the meta-carpophalangeal (MCP), proximal interphalangeal (PIP) and distal interphalangeal (DIP) joints respectively. Ohol S. S. and Kajale S. R. [9], adopt a Biomimetic approach for the gripper design because the stable grasp can only be achieved with multi-fingered grippers. This work provides information on design of Multi-fingered Robot Gripper (MRG) with biomimetic approach. The study elaborates various aspects of design while developing the universal dexterous grasping system.

Ramasamy and Arshad [10] presented technique to simulate a robotic hand that emulates the shape and performance of a human hand (i.e. palm and fingers section). The graphic design is used as a foundation to find the kinematics and dynamic properties of the robotic hand. The paper gives insight to find the properties such as velocity, acceleration and torque for a desired movement or coordinates of the robotic hand graphics.

E.A. Al-Gallaf [11], presents a novel neural network for dexterous hand-grasping inverse kinematics mapping used in force optimization. This is done by considering the inverse hand Jacobian, in addition to the interaction between hand fingers and the object. Their neural-network approach has the advantages that the complexity for implementation is reduced, and the solution accuracy is increased, by avoiding the linearization of quadratic friction constraints. Simulation results show that the proposed neural network can achieve optimal grasping force.

Jack et al. [12] use feed-forward neural networks to solve the inverse kinematics problem which is examined for three different cases. A closed kinematic linkage is used for mapping input joint angles to output joint angles. A three-degree-of-freedom manipulator in 3D space is used to test mappings from both Cartesian and spherical coordinates to manipulator joint coordinates. This paper also shows the use of a new technique which reduces neural network mapping errors with the use of error compensation networks. Ohol and Kajale [13] focused on enhancing the grasping ability with better sensors backup, which can enable the robot to deal with real life situations.

to design gripper by experimenting with various designs for developing the universal dexterous grasping.

Muhammad E. Abdalla, et al. [14], present a joint-space torque control law that demonstrates both a decoupled and significantly faster response than an equivalent tendon-space formulation. A tension distribution algorithm is presented here to allocate forces from the joints to the tendons. The control law and tension distribution algorithm are implemented on the robotic hand of Robonaut-2.

Jasper Schuurmans et al. [15] discussed the optimization of the ratio between highest and lowest force on the proximal phalanges from 4.0 to 2.9 which tend to drive objects out of the grasp when the finger flexes. An extra bi-articular tendon was added to the mechanism, which further improved this ratio to 1.5 with stably grasps and holds objects.

Guan Yisheng and Zhang Qixian [16], investigate manipulation of an object interacting with the environment. Position manipulation was accomplished by three kinematic algorithms, and force manipulation was fulfilled through position control. The feasibility and efficacy of the proposed approach have been verified experimentally on Hkust Hand.

Nakamura and Yamane [17] explore the dynamic computation of structure varying kinematic chains which imply mechanical link systems whose structure may change from open kinematic chain to closed one and vice versa. The computation is developed on the foundation of the dynamics computation algorithms established in robotics, which is superior in efficiency due to explicit use of the generalized coordinates to those used in the general-purpose motion analysis softwares.

Saha [18] discusses constrained dynamic equations of motion of serial multi-body systems consisting of rigid bodies in a serial kinematic chain. Armstrong and Green [19] presented the dynamics of articulated rigid bodies, an efficient method for solving their equations of motion, and a technique for developing human figure models based on these dynamics. They developed the human figure model and showed that these equations can be solved almost in real time.

Al-Gallaf [20] demonstrates the proposed algorithm for a four fingered robot hand motion, where inverse hand Jacobian plays an important role in the hand dynamics. This paper investigates the employment of a neurofuzzy system for a multi-finger robot hand manipulation tasks. The developed neurofuzzy system approach has been trained for several object training patterns and hand postures within a Cartesian based palm dimension.

Rajko Tomovic et al. [21], presented an approach to synthesizing grasping strategies for multi-fingered robot hands,

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based on biological principles. The fundamental idea behind this approach is reduction of the dimensionality of the world by concentrating on target description using geometric primitives, standard grasping configurations and specific strategies for global and local control.

Antonio Bicchi and Vijay Kumar [22] presented a survey of work in robotic grasping over the last many years. The paper focused on issues that are central to the mechanics of grasping and the finger-object contact interactions. In addition, the review mainly addressed research that has established the theoretical framework for grasp analysis, simulation and synthesis.

Laliberte et al. [23] present the development of self adaptive and reconfigurable hands which are versatile and easy to control. These hands have three fingers and each of the fingers has three phalanges. The reconfigurability of the hands is obtained by reorienting the fingers. The design of a three-degree-of-freedom (dof) under-actuated finger, used in all the hands, is

first introduced. A first hand, which has 12 DOFS and 6 motors is then presented. Subsequently, by including underactuation among the fingers and coupling their orientation, a second hand with 10 DOFS and 2 motors is obtained. Finally, control issues and experimental results are presented in the paper.

II. SOLID MODELFigure 3 illustrates the solid model of the proposed robot hand. It has four fingers; three fingers are in series and other one opposes the middle of three series fingered. There are three phalanges (links) in each finger. The palm link has fixed joint and consider being the base. Median and distal links have one degree of freedom (dof) rotational joints. The material selected for the hand prototype is aluminum.

Figure 4 shows the model of a finger which has four frames attached to its joints. The base frame is referring the fixed joint, which is indicated as X0, Y0, Z0. X1, Y1, Z1 and X2, Y2, Z2 are representing joint 2 and joint 3 respectively, whereas X3,Y3, Z3 is representing the fingertip position.

III. FORWARD KINEMATICSForward kinematic is used to determine the position and orientation of the fingertip relative to the robot base coordinate

Figure 3. Solid model of the proposed hand.

Figure 4: Model of one Finger.

Figure 5. Denavit Hartenberg (DH) frame [1].

system. The derivation of forward kinematic equation is done as follows.Letθi = Joint angle of the finger di = joint distance of the finger ai-1 = link length of the each joint ai-1 = link twist angle.

The following Homogeneous transform equations are used to determine the transform between base frame X0, Y0, Z0 to the finger tip frame X4, Y4, Z4. Equation (1) is the generalized equation representing the transformation between the frames i-1 and i.

MULTI-FINGERED ROBOTIC HAND

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(1)

Forward Kinematic is used to determine the position and orientation of multi fingered robotic hand to determine the position and orientation of the robot hand relative to the robot base (Palm) coordinate system. The derivation of forward kinematic equation based on following Table1.

TABLE 1 FINGER PARAMETERS

i θi di ai-1 αi-11 θi 0 0 0

2 θ2 0 l1 (MCP) 0

3 θ3 0 l2 (PIP) 0

4 θ4 = 0 0 l3 (DIP) 0

−

=

100001000000

11

11

10 CS

SC

T

(2)

−

=

1000010000

0

22

122

21 CS

lSC

T

(3)

−

=

1000010000

0

33

233

32 CS

lSC

T

(4)

Therefore, we can calculate

30

52

21

10

30 TTTTT = (5)

++−

=

10000100

00

12211123123

12211123123

30 SlSlCS

ClClSC

T

(6)

=

100001000010

001 3

43

l

T

(7)

Therefore, the forward kinematic for the fingers of robot hand are given by:

43

32

21

10

40 TTTTT = (8)

++++−

=

10000100

00

123312211123123

123312211123123

40 SlSlSlCS

ClClClSC

T

(9)

IV. INVERSE KINEMATICSFor inverse kinematic, we are given Cartesian coordinates, x, y, and φ. We will be finding the value for θ1, θ2, θ3

such that, φ = θ1, θ2, θ3 (10)

Inverse kinematics has multiple solutions for a specific position and orientation of the finger tip. If there is a no solution that means the finger cannot attain the given position and orientation because it lies outside of the finger workspace. The existence or nonexistence of a kinematic solution defines the workspace of a given finger.

Let the given orientation be

(11)

(12)

Figure 6. Flexion angles of fingers.

First of all we compare equation (6) and (12) for the fingers.

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(13)

(14)

Squaring both side and adding equation (15) and (16) we have to eliminate θ1 + θ2

(15)

Equation (15) is in similar form of

(16)

Let (17)

(18)

i.e.,

(19)

(20)

And by using above there are two solutions for θ1

(21)

(22)

(23)

Squaring and adding again equation (15) and (16) we eliminate θ2

(24)

Also we can calculate θ3

(25)

(26)

V. SOME FINDINGS OF REVIEWThe report [3] has not developed the kinematic and dynamic equations for four-fingered robotic hand and the computation of their dynamics has not been discussed in literature. The study [4] limited to the movement of each joint in shoulder, wrist, elbow and finger complexes and has not done any analysis on the hand finger. The methodology and analysis of human upper arm of the paper [5] can be use and incorporate to the any fingered robotic hand. The three most significant functions of the human hand are to explore, move, and to grip objects. The paper [6] left explore and move function of the human hand. Also it can use for modeling of many fingered robotic hand.

The paper [7] has not considered nonlinear properties such as the effect of the Coriollis and centrifugal term. For the design of the controller of such an arm, this nonlinearity is very important. The results of the paper [8] have not published in till now. Other work such as Newton Euler formulation has not been used. The presented mechanism [9] posses scope of development. It can grip odd size and odd shape object, and further it can be developed for universal gripper system. The grasp system can be designed to get perfect grasp points using a vision sensors input can offer a universal biomimetic gripper system.


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The results presented in paper [10] will be helpful in utilizing the existing graphic software for conducting robotic hand simulation, and understanding how to relate the kinematic and dynamic analysis to the actual simulation procedure. The article [11] is computing both the optimal set of fingertip force distribution and an updating mechanism for the interrelated kinematics relation in a multi-fingered robot hand system. The paper [12] has not used an open kinematic linkage for mapping input joint angles to output joint angles. The structure-varying kinematic chains are commonly found in computing human and animal motions, the computation of their dynamics has not been discussed in literature [17]. The work [19] suggests a number of topics for further research. One possible topic is reducing the time required to solve the equations of motion.

VI. CONCLUSIONThis paper presented a survey of work in kinematic and dynamic modeling and analysis of multi-fingered robotic hand over the last many years. It is not possible to justify to all the work in this area, particularly throughout the field and its dexterous manipulation, explore, move, and to grip objects. We presented here a survey on kinematic and dynamic modeling and analysis of multi-fingered robotic hand.

In addition, the review mainly addressed research that has established the theoretical framework for kinematic and dynamic analysis, simulation and synthesis. Because of the limitations on space, we have not given the algorithmic aspects and the applications the attention that they deserve. We hope that this paper find application for further work in the field of robotics hand modeling and analysis.

VI. REFERENCES[1]. J. Denavit and R.S. Hartenberg, “A Kinematic Notation for

Lower-Pair Mechanisms Based on Matrices,” Journal of Applied Mechanics, pp. 215—221, June 1955.

[2]. John J.Craig. Introduction to Robotics. 2nd ed. Pearson Education International.

[3]. Victor J. Johnson and Gregory P. Starr., “Kinematic and Dynamic Analyses of the Stanford/ JPL Robot Hand”, Sandia report presented by Sandia National Laboratories, November 1987.

[4]. S. Parasuraman and Ler Shiaw Pei., “Bio-mechanical Analysis of Human Joints and Extension of the Study to Robot”, World Academy of Sc., Engg and Tech, 2008.

[5]. Valentin Grecu, et al., “Analysis of Human Arm Joints and Extension of the Study to Robot Manipulator”, Proc. International Multi-Conference of Engineers and Computer Scientists 2009, Volume II IMECS 2009, March 18-20, 2009, Hong Kong

[6]. Izzeldin Ibrahim Mohamed Abdelaziz., “A Low-Cost Smart Glove for Hand Functions Evaluation”, International Journal of Robotics and Automation, Volume 3, No. 1, March 2014, pp. 39~51.

[7]. Kazuhiro Kosuge, Katsuhisa Furuta., “Kinematic And Dynamic Analysis Of Robot Arm”, IEEE pp-1039-1044, 1985

[8]. Wan Faizura Binti Wan Tarmizi, et al, “Kinematic and Dynamic

Modeling of a Multi-Fingered robot Hand”, International Journal of Basic & Applied Sciences, Volume 9, No. 10, pp. 89-96.

[9]. OHOL S. S. and KAJALE S. R., “Biomimetic Approach for Design of Multifingered Robotic Gripper(MRG) and Its Analysis for Effective Dexterous Grasping”, Proc. 2009 International Conference on Machine Learning and Computing IPCSIT, Volume 3 (2011), pp. 213-221, Singapore.

[10]. S.Ramasamy and M.R.Arshad,“Robotic hand simulatlon with kinematics and dynamic analysis”, IEEE (2000) page-178-183

[11]. E.A. Al-Gallaf, Multi-fingered robot hand optimal task force distribution Neural inverse kinematics approach, International Journal of Robotics and Autonomous Systems 54 (2006) page-34–51.

[12]. H. Jack, D. M. A. Lee, R. O. Buchaland W. H.Elmaraghy, Neural networks and the inverse kinematics problem, Journal of Intelligent Manufacturing (1993) 4, 43-66.

[13]. S. S. OHOL, S. R. KAJALE, Simulation of Multifinger Robotic Gripper for Dynamic Analysis of Dexterous Grasping, Proc. World Congress on Engineering and Computer Science, October 2008, San Francisco, USA.

[14]. Muhammad E. Abdallah, et al., Applied Joint-Space Torque and Stiffness Control of Tendon-Driven Fingers, Proc. IEEE-RAS International Conference on Humanoid Robots, Nashville, TN, USA, December 2010.

[15]. Jasper Schuurmans et al., Grasp force optimization in the design of an underactuated robotic hand, Proceedings of the Proc. IEEE 10th International Conference on Rehabilitation Robotics, 2007. Noordwijk, The Netherlands pp.776-782

[16]. Guan Yisheng, Zhang Qixian, hybrid position/ force manipulation of multifingered hand , Chinese Journal Of Aeronautics, Volume 11, No.2, pp-143-151, May 1998.

[17]. Yoshihiko Nakamura and Katsu Yamane, Dynamics Computation of Structure-Varying Kinematic Chains and Its Application to Human Figures, IEEE Trans. Robotics and Automation, Volume 16, No. 2, April 2000 pp. 124-134.

[18]. S. K. Saha, Dynamics of Serial Multibody Systems Using the Decoupled Natural Orthogonal Complement Matrices, Trans. ASME, Volume 66, pp-986-996, December, 1999.

[19]. William W. Armstrong and Mark W. Green, The dynamics of articulated rigid bodies for purposes of animation , The Visual Computer (1985) I: pp-231-240.

[20]. E. A. AL-GALLAF, Neurofuzzy Inverse Jacobian Mapping for Multi-Finger Robot Hand Control, Journal of Intelligent and Robotic Systems, Volume 39, pp-17–42, 2004.

[21]. Rajko Tomovic, et al, A Strategy For Grasp Synthesis With Multifingered Robot Hands, Proc. IEEE Conference Robotics and Automation, pp-83-89, 1987.

[22]. Antonio Bicchi and Vijay Kumar, Robotic Grasping and Contact: A Review , Robotics and Automation, 2000. Proc. IEEE International Conference. ICRA’00. pp-348-353

[23]. Thierry Laliberte, et al., Underactuation in robotic grasping hands , Machine Intelligence & Robotic Control, Volume 4, No.3, pp-1–11, 2002.

[24]. Panagiotis K. Artemiadis and Kostas J. Kyriakopoulos , “EMG-based Position and Force Control of a Robot Arm: Application to Teleoperation and Orthosis.

[25]. Okada, T.; Tsuchiya, S. : “On a Versatile Finger System”, Proc. 7th Int. Symposium of Industrial Robots, 1977.

[26]. Okada, T.: “Computer Control of Multijoined Finger System

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for Precise Object Handling“, IEEE Trans. Systems, Man and Cybernetics, Volume 12, No.3, May/June 1982.

[27]. Jacobson, S.C.; Wood, J.E.; Knutti, D.F.; Biggers, K.B.: “The Utah/MIT Dextrous Hand: Work in Progress”, Proc. First Int. Conf. on Robotics Research, MIT Press, 1984.

[28]. Jacobson, S.C. et.al.: “Design of the Utah/MIT Dextrous Hand”, Proc. IEEE Int. Conf. on Robotics and Automation, 1986.

[29]. Narasiham, S.: “Dextrous Robotic Hands: Kinematics and Control”, Master thesis, Department of Electrical Engineering and Computer Science, MIT, 1988.

[30]. Salisbury, K.; Brock, D.; Chiu, S.: “Integrated Language, Sensing and Control for a Robot Hand”, Proc. Int. Symp. on Robotics Research, MIT Press, 1986.

[31]. Nguyen, V.: “Constructing Stable, Force-Closure Grasps”, Master Thesis, Department of Electrical Engineering and Computer Science, MIT, 1986.

[32]. Arbib, M.A.; Iberall, T.; Lyons, D.: “Coordinated Control Programs for Movements of the Hand” Center of Systems Neuroscience and Laboratory for Perceptual Robotics, COINS Technical Report 83-25, Massachusetts, 1983.

[33]. Lyons, D.M.: “A simple Set of Grasps for a Dextrous Hand”, Proc. IEEE Int. Conf. on Robotics and Automation, 1985.

[34]. Iberall, T.: “Grasp Planning for Human Prehension”, Proc. Int. Joint Conf. on Artificial Intelligence, 1987.

[35]. S.C. Jacobsen, E.K. Inversen, D.F. Knutti, R. T. Johnson and K.B. Biggers, “Design of the Utah/MIT Dexterous Hand, Proc. 1986 IEEE International Conference on Robotics and Automation, pp 1520-1532, 1986.

[36]. Man Zhihong, Robotics for Computer Engineering Students, Prentice Hall, 2004.

[37]. J. K. Salisbury M.T. Mason: “Robot Hands and the Mechanics of Manipulation”, MIT Press, Cambrige, MA, 1985.

[38]. Pernell A. Jordan, “Feedback Control Of A Three-LinkPlanar Under-Actuated Manipulator using A “Surge” Velocity”, Thesis of Naval Postgraduate School Monterey, California, September 1995.

[39]. Cole, A.; Hauser, J.; Sastry, S.: “Kinematics and Control of Multifingered Hands with Rolling Contact”, Proc. IEEE Int. Conf. on Robotics and Automation, 1988.

[40]. Hsu, P.; Li, Z.; Sastry, S.: “On Grasping and Coordinated Manipulation by a Multifingered Robot Hand” Proc. IEEE Int. Conf. on Robotics and Automation, 1988.

[41]. J.M. Hollerbach and T. Flash, “Dynamic Interactions Between Limb Segments During Planar Arm Movements,” Biol. Cyber. Volume 44, No. 1, pp. 67-77, 1982.

[42]. R.P. Paul and C.N.Stevenson, “Kinematics of Robot Wrists,” International Journal of Robotics Research, Volume 2, No. 1, 1983.

[43]. M.H. Raibert and J.J. Craig, “Hybrid Position/Force Control of Manipulators”, Trans. ASME J. Dyn. Sys., Measurement, Contr., Volume 103, No. 2, pp. 126-133, 1981.

Md. Zafer Hussain received the B. Tech. degree in Mechanical Engineering from Aligarh Muslim University Aligarh, Uttar Pradesh in 2004, and the M. Tech. degree in Mechanical Engineering with specialization in Machine Design from the same university in 2007. Pursuing Ph.D. in Mechanical Engineering from Jamia Millia Islamia (A Central University), New Delhi. His teaching and research areas include Vibration, Robotics, Mechatronics, Mechanism and Automation, Nonlinear Dynamics, System Identification, etc. He is currently writing a Textbooks and authored many research papers.

Dr. M. Suhaib received the B.Sc. Engg degree in Mechanical Engineering from the Aligarh Muslim University, Aligarh, U.P, in 1990, the M.Sc. Engineering degree in Machine Design from the same university in 1993, and the Ph.D. degree in Mechanical Engineering from the Jamia Millia Islamia (A Central University), New Delhi, 2004. Currently, He is a Professor of Mechanical Engineering at Jamia Millia Islamia. His teaching and research areas include Robotics, Mechatronics,

Mechanism and Automation. He has authored/co-authored two textbooks and approximately fifty research papers.


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Overview on Burr Formation, Simulation and Experimental Investigation of Burr size — based on Taguchi Design of Experiments during Drilling of Alluminium 7075 Alloy

Reddy Sreenivasulu1 and Chalamalasetti Srinivasa Rao2

1Department of Mechanical Engineering, R.V.R. and J.C. College of Engineering , Chowdavaram, Guntur, Andhra Pradesh, India

2Department of Mechanical Engineering, University College of Engineering, Andhra University, Visakhapatnam, Andhra Pradesh, India

[email protected], [email protected]

Abstract — The drilling of metals produces undesirable projections at the surfaces of holes called burrs, which are very costly to remove from the work piece. Burr formation in drilling operations causes products to be rejected or sent for deburring. Since deburring is a costly and non-value-added operation, the understanding and control of burr formation is a research topic with high relevance to industrial applications. This study focuses on the burrs formed in drilling of Al 7075 alloy at the exit side of the work piece. The results of this research show that the height and thickness of the burr that can be controlled by proper selection of drill bit that consists of suitable geometric parameters. In this experimental study, L27 orthogonal array of Taguchi design method, analysis of variance (ANOVA) was taken to find out the influence of process parameters on the response. Predicted values are finally checked for accuracy through a confirmation test. Confirmatory experiments were conducted for burr height and burr thickness, corresponding their optimal setting of process parameters to validate the used approach, obtained the values of 0.158 mm, 0.124 mm for burr height and burr thickness respectively.

Keywords: Burr height, Burr thickness, Burr minimization, Taguchi method, ANOVA

I. INTRODUCTIONDRILLING is a machining process used to create or enlarge holes into or through a workpiece material. The process is performed with the use of a drill, which works by rotating at a fast speed while simultaneously being fed into the workpiece, removing incremental amounts of workpiece material. The drill itself, which performs the cutting action, has multiple cutting edges and flutes running along its length that allow the chips of workpiece material to be carried away. During the drilling process, burrs form on both the entry and exit surfaces as a result of plastic deformation of the workpiece material. Burrs are simply small amounts of attached material that protrude from the original entry and exit surfaces around the drilled hole. They are generally unwanted, and commonly need to be removed depending on the specific desired part geometry. If they are not removed, they can cause misalignment with

adjacent parts. The burrs can also get detached from the surface and get trapped between mating surfaces leading to three-body abrasion and eventual failure of the assembly, among numerous other potential problems.

Literature on burr formation: The demands placed by designers on workpiece performance and functionality are increasing rapidly. Important aspects of manufacturing’s contribution to the fulfillment of these demands are the conditions at the workpiece edges [1]. The presence of burrs on the edges of parts after machining, which may bring about a number of problems, makes deburring a necessary part of the production process.

The proper way of burr removal, the conditions of deburring, and the deburring cost depend on the part’s features and the burr dimensions [2]. Not only deburring is a non-value-added process, but in many cases increasing burr formation is a key factor of cutting tool wear and leads to replacement of tools. Burrs do not have to be removed from a workpiece for functional reasons, there are still two dangers remaining. Firstly, burrs are often quite sharp and can lead to small finger injuries for assembly workers. Secondly, burrs which initially stick to a part can become loose during operation of a product and cause damage later on. In conventional drilling, burr formation can be changed by varying the drill’s geometry [3]. Its formation is due to a plastic deformation on a ductile material.

This imperfection can be formed at the entrance as at the exit of a hole, although its appearance is more common on the last one. Presently, there are various international and national standards as well as proprietary standards for describing burrs and evaluating the quality of component edges. For thousands of years there was no word for a ‘‘burr’’ formed by machining, but Erasmus Darwin, grandfather of Charles Darwin, a naturalist and poet, appears to be the first person to mention ‘‘burr’’ in writing (1784). In the Oxford English Dictionary a burr is described as a rough ridge or edge left on metal or other substance after cutting, punching, etc.; e.g. the roughness

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produced on a copper-plate by the graver; the rough neck left on a bullet in casting; the ridge left on paper, etc., by puncture [1]

The ISO 13715 defines the edge of a workpiece as burred if it has an overhang greater than zero. Ko and Dornfeld [4] bases his work on this definition and defines a burr as an ‘‘undesirable projection of material formed as the result of plastic flow from a cutting or shearing operation’’. A comprehensive definition can be found in [5]. A burr is a body created on a workpiece surface during the manufacturing of a workpiece, which extends over the intended and actual workpiece surface and has a slight volume in comparison with the workpiece, undesired, but to some extent, unavoidable.

Kim et al. [6] categorize drilling burrs as uniform burr with or without a drill cap, crown burr or petal burr according to their shapes and formation mechanism. Two types of burrs, uniform burr (type I: small uniform burr, type II: large uniform burr) and crown burr, for stainless steel and three types of burrs, uniform burr (type I: small uniform burr, type II: large uniform burr),

transient burr, and crown burr, for low alloyed steel were found as shown in (Fig. 1).

Literature on parameters that influence burr formation: It is necessary to differentiate investigations which cover burr form and others that cover the topic of minimizing burrs. Gillespie and Blotter [7] already observe that burrs cannot be prevented by changes in feed, speed, or tool geometry alone. Still, the size of burrs produced can be minimized significantly by choosing appropriate machining parameters. To minimize and prevent burrs it is necessary to examine the entire cutting process. It is not sufficient to change only one process parameter as there are many influences between the parameters. Burr formation is affected by various parameters. Major effects are workpiece material, tool geometry, tool wear, tool path and machining parameters. In most cases a change of workpiece material is not possible. As to an improved tool path, this approach is also limited, as complex geometries would require burr optimized tool paths that prolong cycle time as negative effect.

Link [8] point out that burr formation parameters cannot reliably be separated into direct and indirect factors due to the complex connections and relations between the numerous influencing variables (Figure 2). Wang and Zhang [9] investigate cutting burrs. The main factors of cutting direction burr formation are cutting parameters, the shape of the workpiece end, cutting tool geometry and workpiece material. The burr height in cutting direction is reduced with the increase in the depth of cut, feed, cutting edge angle and back rake angle. An increase of corner radius leads to increasing burr height.

Literature on simulation of burr formation: Due to the difficulties of analytical approach, extensive experiments have been done by several researchers. Gillespie [10] identified three stages of burr formation and Stein [11] classified burr geometry and identified burr influential factors for burr formation statistically. Kim [12] developed a control chart for prediction of burr type and size in drilling of stainless steel by split point twist drills. The further experiments to generate data on several aspects of hole quality will be done by Dechow [13]. However, understanding the drilling process mechanism by experiments has a limited insight. A simplified analytical model was proposed by Sofronas [14] and Lee [15] employed various feed control schemes to minimize burr size using the thrust force based on the Sofronas’ model.

Both models cannot predict the burr geometry because a closed form analytical solution for drilling burr formation is extremely difficult to derive. A finite element model of drilling burr formation process, Fig 3(a), is developed by Guo [16]. The nonlinear thermoelastic- plastic model accounts for dynamic effects, strain hardening, strain rate, automatic mesh contact with friction, material ductile failure and temperature-mechanical coupling simultaneously. Figure 2. Factors governing burr formation.

Figure 1. Typical drilling burr types according to CODEF.

BURR FORMATION

26


Guo’s finite element simulation gave an insightful description of drilling burr formation. He divided drilling formation mechanism into four stages: initiation, development, pivoting point and formation stages, Figure 3(a). Local fully plastic deformation initiates a burr at the edge of the workpiece with the initial plastic hinge formation within the workpiece. The development stage is characterized by smooth transition from cutting to plowing along drill lips due to the combination of shearing and bending. The pivoting point stage represents the formation of a stationary plastic hinge in the radial direction.

The burr thickness is largely determined by the distance between the pre-defined machined surface and the pivoting point. Finally, the burr formation stage represents the cap formation and removal, and the subsequent material roll-over process which continues to form the final burr. Cap formation

shown to be useful, such codes are not being used today in a manner that could have maximum potential impact on the drilling process due to the high cost of preparation for the process simulation by finite element analysis (FEA). With strong demand in industry for burrless hole making, it is desired to integrate FEA models with drill CAD to evaluate drill performance in the drilling process and fully utilize the benefits of this numerical tool in concurrent engineering. The complexity and various geometry parameters of a drill need a time consuming work to model and modify it. Hence, an integrated CAD/FEA system for drill design and drilling burr formation process (Fig.3b) was proposed by Guo [17].

After reviewed from references, finally found that burr formation is a complex mechanism to analyze and to prevent that, many researchers conduct their work related to burr minimization schemes towards basic machining processes such as turning, milling, grinding and drilling, but 100% not prevent to form it that is identified. So the objective of this study is to investigate the effects of the drilling parameters on burr size and is to determine the optimal drilling parameters using the taguchi design method.

II. EXPERIMENTAL INVESTIGATIONMaterial: The composition of Alluminium alloy 7075 consists of Aluminum (Al) 87.2 to 91.4 %, Zinc (Zn)5.1 to 6.1 %,Magnesium (Mg)2.1 to 2.9 %, Copper (Cu)1.2 to 2.0 %, Iron (Fe)0 to 0.5 %, Silicon (Si)0 to 0.4 %, Manganese (Mn)0 to 0.30 %, Chromium (Cr)0.18 to 0.28 %, Zirconium (Zr)0 to 0.25 %, Titanium (Ti)0 to 0.2 %, Residuals 0 to 0.15 %. In this study 300x50x10mm rectangular bar was used.

Schematic machining: In this study, the experiments were carried out on a CNC vertical machining center (KENT and ND Co. Ltd, Taiwan make) to perform different size of holes on Al7075 work piece by alter the point and clearance angles on standard HSS twist drill bits and maintain constant helix angle of 45 degrees. Furthermore the cutting speed (m/min), the feed rate (mm/rev) and drill diameter (mm) are varied in this experiment. The burr size (thickness and height) is measured by optical microscope (200 X magnification).

Experimentation as per Taguchi Design Method: The orthogonal array forms the basis for the experimental analysis in the Taguchi method. The selection of orthogonal array is concerned with the total degree of freedom of process parameters. Total degree of freedom (DOF) associated with five parameters is equal to 10 (5X2).The degree of freedom for the orthogonal array should be greater than or at least equal to that of the process parameters. Thereby, a L27 orthogonal array having degree of freedom equal to (27-1) 26 has been considered, which is used to optimize the cutting parameters for burr height and burr thickness, using the S/N ratio and ANOVA for machining of Al 7075 alloy.

Figure 3a. Finite element simulation of burr formation in drilling machining (b) Automatic mesh generation for drill geometry and

CAD/FEA integration.

and removal greatly affect burr size and shape. The burr height is determined by the positions of the pivoting point and the cap formation. The FEM simulation demonstrates the dominant roles of negative shearing and bending mechanisms in the drilling burr formation process.

Although the results of numerical simulation codes have been

(a)

(b)

27

TABLE 1 -- MACHINING PARAMETERS AND THEIR LEVELS

LEVELS FACTORSCutting Speed (rpm) Feed Rate

(mm/min)Drill Diameter (mm) Point Angle

(Degrees)Clearance Angle

(Degrees)A B C D E

1 600 0.3 8 118 42 800 0.5 10 110 63 1000 0.6 12 100 8

TABLE 2 -- PLAN OF EXPERIMENTS BASED ON TAGUCHI ORTHOGONAL ARRAY AND OBSERVED RESPONSES

RUNS TAGUCHI RESPONSE DESIGN TABLE S/N Ratio

Cutting Speed (rpm)

Feed Rate (mm/min)

Drill Diameter(mm)

Point Angle(deg)

Clearance Angle (deg)

Burr Height(mm)

Burr Thickness(mm)

A B C D E R1 R2

1 1 1 1 1 1 0.246 0.167 -1.6257

2 1 1 1 1 2 0.232 0.155 4.4302

3 1 1 1 1 3 0.226 0.150 -7.0661

4 1 2 2 2 1 0.265 0.197 3.7351

5 1 2 2 2 2 0.236 0.157 -4.5443

6 1 2 2 2 3 0.242 0.186 -5.4392

7 1 3 3 3 1 0.216 0.138 -6.1494

8 1 3 3 3 2 0.325 0.230 -4.8018

9 1 3 3 3 3 0.220 0.173 -1.2757

10 2 1 2 3 1 0.296 0.232 -4.4926

11 2 1 2 3 2 0.200 0.148 -1.0974

12 2 1 2 3 3 0.306 0.207 4.9104

13 2 2 3 1 1 0.206 0.145 -4.2678

14 2 2 3 1 2 0.178 0.140 -5.1281

15 2 2 3 1 3 0.165 0.153 2.1128

16 2 3 1 2 1 0.302 0.212 -5.0234

17 2 3 1 2 2 0.197 0.136 -1.8092

18 2 3 1 2 3 0.222 0.209 -6.8246

19 3 1 3 2 1 0.192 0.178 -3.2515

20 3 1 3 2 2 0.187 0.180 -3.3102

21 3 1 3 2 3 0.242 0.222 -4.6745

22 3 2 1 3 1 0.232 0.201 -3.8761

23 3 2 1 3 2 0.207 0.241 -3.6246

24 3 2 1 3 3 0.174 0.152 1.5275

25 3 3 2 1 1 0.164 0.141 -2.7174

26 3 3 2 1 2 0.201 0.158 -4.7837

27 3 3 2 1 3 0.219 0.187 -5.1285

BURR FORMATION

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TABLE 3 -- SIGNAL TO NOISE RATIOS (SMALLER IS BETTER)Level Cutting Speed

(rpm) AFeed Rate

(Mm/Min) BDrill Diameter

(Mm) CPoint Angle

(Deg) DClearance Angle

(Deg) E1 -2.52518 -1.79783 -2.66049 -2.10312 -2.441302 -2.41537 -2.18147 -2.17144 -3.45934 -2.743953 -3.31802 -4.27928 -3.42665 -2.69612 -3.07333

Delta 0.90265 2.48145 1.25522 1.35623 0.63203Rank 4 1 3 2 5

TABLE 4 -- RESULTS OF ANOVA FOR BURR HEIGHTSymbol Parameters DOF SS MS F

A Cutting speed 2 0.00871 0.00435 36.25 significant

B Feed rate 2 0.00292 0.00146 12.16 significant

C Drill diameter 2 0.00218 0.00109 9.08 significant

D Point angle 2 0.00684 0.00342 28.5 significant

E Clearance angle 2 0.00140 0.00070 5.83 significant

Error 16 0.001926 0.00012

Total 26 0.023976

TABLE 5 -- RESULTS OF ANOVA FOR BURR THICKNESSSymbol Parameters DOF SS MS F

A Cutting speed 2 0.0066 0.0033 16.75 significant

B Feed rate 2 0.0027 0.0013 6.598 significant

C Drill diameter 2 0.0029 0.0015 7.614 significant

D Point angle 2 0.00702 0.00351 17.766 significant

E Clearance angle 2 0.0053 0.0027 13.705 significant

Error 16 0.00315 0.000197

Total 26 0.02765

TABLE 6 -- OPTIMAL VALUES OF INDIVIDUAL MACHINING CHARACTERISTICSMachining Characteristics

Optimal combination of parameters

Significant parameters(at 95% confidence level)

Predicted optimum value

Experimental value

Burr height (R1) A1B1C2D1E3 A,B,C,D,E 0.158 0..164

Burr thickness (R2) A3B1C1D1E1 A,B,C,D,E 0.124 0.136

Though similar to design of experiment (DOE), the Taguchi design only conducts the balanced (orthogonal) experimental combinations, which makes the Taguchi design even more effective than a fractional factorial design. By Taguchi techniques, industries are able to greatly reduce product development cycle time for design and production, therefore reducing costs and increasing profit. Finally, confirmation test have been carried out to compare the predicted values with the experimental values confirm its effectiveness in the analysis of

burr size. The machining parameters and their levels are given in Table1. Plan of experiments based on Taguchi orthogonal array and observed responses shown in Table 2.

II. RESULTS AND DISCUSSIONAnalysis of the S/N Ratio: In the Taguchi method, the term ‘signal’ represents the desirable value (mean) for the output characteristic and the term ‘noise’ represents the undesirable value (Standard Deviation) for the output characteristic. S/N

29

ratio used to measure the quality characteristic deviating from the desired value.

The S/N ratio (η) is defined as η = -10 log (M.S.D),

where M.S.D is the mean square deviation for the output characteristic. Table 2 shows the experimental results for observed responses. The S/N ratio table for observed responses is shown in Table 3.

From main effects plot of S/N ratio for, the optimum parameters combination for burr height and burr thickness are A2B1C2D1E1 corresponding to the largest values of S/N ratio for all control parameters. From Table 3, it is observed that feed rate, point angle, drill diameter, cutting speed and clearance angle has the order of influence on burr size during drilling of Al 7075 alloy.

Results of ANOVA: The purpose of the analysis of variance (ANOVA) is to investigate which design parameters significantly affect the quality characteristic. Table 4 shows the results of ANOVA for burr height, cutting speed, feed rate, drill diameter, point angle and clearance angle are the significant cutting parameters for affecting the burr height.

Table 5 shows the results of ANOVA for burr thickness, cutting speed, feed rate, drill diameter, point angle and clearance angle are the significant cutting parameters for affecting the burr thickness.

Significant, Ftable at 95%confidence level is F0.05, 2, 16 = 3.63, F exp ≥ F table

Significant, F table at 95%confidence level is F0.05, 2, 16 = 3.63, F exp ≥ F table

Confirmatory experiments were conducted for burr height and burr thickness, corresponding their optimal setting of process parameters to validate the used approach, obtained the values of 0.158mm, 0.128mm for burr height and burr thickness respectively. Predicted and experimental values of responses are depicted in table 6.

IV. CONCLUSIONThe machining characteristics of Al 7075 alloy have been studied. The primary machining characteristics such as burr height and burr thickness were studied for drilling operation. From S/N Ratio response table, feed rate, point angle, drill diameter, cutting speed and clearance angle has the order of influence on burr size during drilling of Al 7075 alloy.

From S/N Ratio response graph, the combination of parameters having the values of 800 rpm, 0.3 mm/min ,10mm.118 degrees and 4 degrees obtained for cutting speed, feed rate drill diameter, point angle and clearance angle respectively for optimizing burr size.

V. REFERENCES[1]. J.C. Aurich. Burrs, ‘Analysis, Control and Removal’, CIRP

Annals - Manufacturing Technology, Volume 58, pp. 519–542, 2009.

[2]. Andrey Toropov Sung-Lim Ko. “A Model of Burr Formation in the Feed Direction in Turning, International Journal of Machine Tools & Manufacture, Volume 46, pp. 1913–1920, 2006.

[3]. Sung-Lim Ko Jae-Eun Changa, Gyun-Eui Yang. ‘Burr Minimizing Scheme in Drilling’, Journal of Materials Processing Technology, Volume 140, pp. 237–242, 2003.

[4]. Ko SL, Dornfeld DA.. ‘A Study on Burr Formation Mechanism’, Trans. ASME Journal of Engineering Materials and Technology, Volume 113, No. 1, pp. 75–87, 1991.

[5]. Beier HM. Handbuch Entgrattechnik: Wegweiser zur Gratminimierung und Gratbeseitigung fur Konstruktion und Fertigung. Hanser Verlag (1999).

[6]. Kim J, Min S and Dornfeld D.,’Optimization and Control of Drilling Burr Formation of AISI 304L and AISI 4118 Based on Drilling Burr Control Charts’, International Journal of Machine Tools & Manufacture, Volume 41, No. 7, pp. 923–936, 2001.

[7]. Gillespie LK and Blotter PT, ‘The Formation and Properties of Machining Burrs’, Trans. ASME Journal of Engineers for Industry 98(1976):66–74.

Figure 4. Images of drilled holes as per Taguchi design.

Figure 5. Response graph of S/N Ratio.

OVERVIEW ON BURR FORMATION

30


[8]. Link R (1992) Gratbildung und Strategien zur Gratreduzierung, Dissertation, RWTH Aachen.

[9]. Wang GC, Zhang CY, ‘Study on the Forming Mechanism of the Cutting- Direction Burr in Metal Cutting’, Key Engineering Materials 259–260: pp.868–871, 2004.

[10]. Gillespie, L.K., “Burrs Produced by Drilling”, Bendix Corporation, Unclassified Topical Report BDX-613- 1248, December 1975.

[11]. Stein, J.L., “Burr Formation in Precision Drilling of Stainless Steel”, Ph.D. Dissertation, UC Berkeley, April 1989.

[12]. Kim, J., “Control Chart of Drilling Exit Burr in Stainless Steel”, LMA Report, 1998.

[13]. Dechow, H., “Influence of Tool Geometry on Hole Quality when Drilling Ti-6Al-4V”, LMA Report, 1998.

[14]. Sofronas, A., “The Formation and Control of Drilling Burrs”, Ph.D. Dissertation, The University of Detroit, 1975.

[15]. Lee, G.B., “Digital Control for Burr minimization in Drilling”, Ph.D. Dissertation, UC Berkeley, April 1989.

[16]. Guo, Y., “Finite Element Modeling of Drilling Burr Formation Process”, M.E. Dissertation, UC Berkeley, 1997.

[17]. Guo, Y. and Dornfeld, D.A., “Integration of CAD of Drill with FEA of Drilling Burr Formation”, Trans. NAMRI/SME, Volume 26, pp. 201-206, 1998.

Reddy Sreenivasulu is an Assistant Professor in the department of Mechanical Engineering, R.V.R & J.C College of Engineering (Autonomous) Guntur, AndhraPradesh, India. Rreceived B.Tech (Mechanical Engineering) degree from the Regional Engineering College, Warangal in the year 1997 and M.E degree from the University College of Engineering, Osmania University, Hyderabad in Automation & Robotics in the year 2003. He has 15 years of teaching experience. His area of research

interest includes design of experiments, robotics, modeling and analysis of manufacturing

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An Empirical Investigation of the Various Antecedents of the Customer Satisfaction in Case of Mobile Services — A Comprehensive Study of Haryana Province in India

Vishal GargDepartment of Management, Thapar University, Patiala, Punjab 147004 India

[email protected]

Abstract — Mobile platform is heralded as the next frontier for modern business creating entirely new paradigms for interactive marketing initiatives in developing countries like India. The telecom sector industry is characterized by stiff competition and alternative service providers with the implementation of Mobile Number Portability, consumers have the freedom to choose from among the available alternatives. The research had two objectives. First, it sought to identify factors that influence individual consumer’s choice of a mobile phone service provider in the mobile telephone industry. Second, it sought to assess the relative importance of the pertinent factors. In undertaking the study, individual users of mobile telephone services within Haryana were targeted. Primary data was collected using a semi – structured questionnaire. The survey instrument was administered directly to the respondents by the researcher within the selected areas. Out of the targeted 125 respondents, the researcher managed to obtain a response rate of 88%. The results of the study showed that 30% of the respondents found costs of the services offered to be the most important factor while 85% stated that countrywide network coverage was the most important factor. Many Statistical tools (SPSS 20) were used to determine the factors and examining their relationship of those factors towards the consumer’s perception in selecting an operator’s services. From the result, it is revealed Network Quality is the most important factor followed by Call Price, service availability and promotion.

Keywords: Mobile Telecom Service Provider, Consumer Perception, Service Quality, Promotion, Customer Retention, Customer Loyalty, Service Quality, Customer Satisfaction, Telecom Sector

I. INTRODUCTIONMOBILE phone service is viewed as a commodity by customers all over the world. The telecommunications sector is changing radically in this competitive era. The changes are driven by a combination of market, competitors, business and various technological forces. There are many factors that influence the Telecom Sector like Globalization, Customer Awareness, Quality, Pricing and Government Policies. Customers are always important for any business be it manufacturing or service industry. With the high rate of competition in every market, it is critical to retain the customer and convert them into loyal customers.

With the increase in the availability of options and information to the customers today, it has become a cumbersome job to get the customers back to you in the telecom sector. Quality service is becoming very important in customer retention in the mobile telephony industry. Now-a-days, customers are willing to shell out extra money for good service quality. So customer satisfaction plays a vital role for any manufacturing or service sector industry. With the ingress of more and more mobile service providers it has become very complex in making of decision as regard which service or product to use.

Customer satisfaction is one of the most important factors for increasing the organization customer base, goodwill, repurchases likelihood and profits. It clearly states that the mobile service providers should satisfy their customers so that they become loyal and remain with operators. The main outcome of customer satisfaction is the customer loyalty, and a company having large share of loyal customers, then there is increase in repurchase rate, greater cross buying potential, higher price tolerance, positive recommendation behaviour and lower switching tendencies. Old and satisfied customers are sometimes less sensitive to the price and are loyal to the service provider. A retained customer will always show resistance to competitors’ enticement and offers and will be able to give both solicited and unsolicited referral.

Indian telecommunication industry contributes significantly towards the country’s development and plays an integral part in the lives of many. Tele-communication contributes significantly to the GDP, a contribution of 400 billion US Dollars was made in the year 2014. There has been an unprecedented upsurge in the penetration rate within the mobile telecommunication industry. Penetration rate in India was standing at 78.73 in 2014 which was regarded among the highest rate in the world. A but obvious truth in the business world is that competitors always look to steal others’ customers and many customers are in constant search for a better deal as they are not so loyal to the mobile service provider. Customer attrition rates range from seven percent annually in some industries with high exit barriers, like banking and insurance, to nearly 40 percent in the mobile phone industry.

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Reducing the customer “churn” rate by even one percent will add millions of rupees to any mobile service provider. As it is more expensive to acquire customers than to retain them, an effective customer retention strategy is crucial to a company’s success and increases loyalty among the customers. Customer retention is considered important when loyalty among the customer is decreasing and sales cycles are aggravating the business environment. Under these conditions, losing customers to a competitor would impact organization’s profitability and growth in a negative approach. Preventing current customers from switching to other service providers is a very hard task.

less relevant to the prediction of subscribers’ retention. Bolton (1998) found that there exists a considerable positive effect of overall customer satisfaction of mobile service subscriber on the duration of the relationship. The concept of measuring the customer satisfaction will serve the same purpose of determining the customer perception regarding their mobile service provider. Different researchers are of the view that the customers are created and maintained through marketing strategies. So, the marketing team is the real face of the organization in every service industry. As per (Karjaluoto et al. 2005), price, brand, word of mouth communication, and quality tends to have the most influential factors affecting the actual choice regarding mobile service providers. Some researchers have put forward (Eric and Bright 2008) that the first and the most important factor is reliable quality of the mobile service provider.

M. Satish, K.J Naveen, V. Jeevananthan, (2011) identified different factors that influence the consumers to switch the different mobile service providers. Their research concluded that there is a relation between switching the service provider based on the factors like poor network coverage, frequent network issues, call rates, influence from family and friends and word of mouth communication.Figure 1. Customer Life Cycle.

During lifetime of the service, customers have many opportunities to switch to different mobile service providers (competitor offers, sales promotions, etc.), and many events within the established relationship are likely to cause service relationship deterioration and dissolution. Mobile Service switching is mainly due to critical incidents, such as strategies by competitors, inappropriate employee responses to service failures, pricing concerns, core service failures, service encounter failures, unethical practices, lack of convenience, or changes in the consumer’s or service provider’s situation. Effective CRM strategies can be used to enhance retention among subscribers. If customer satisfaction is considered as the primary driver of retention, then a firm should improve product or service quality or offer better prices or provide some useful and innovative services. Otherwise, if affective or calculative commitment is treated as more important, then a firm should build direct relationships with customers.

II. LITERATURE REVIEWAs per (Johnson and Fornell 1991), Customer satisfaction is defined as a customer’s overall evaluation of the performance of an offering to date The overall satisfaction always have a strong and positive effect on customer loyalty intentions covering a wide range of product and service categories, including telecommunications services (Fornell 1992; Fornell et al. 1996). Customer Satisfaction also contains a high level of significant affective component, which is created through repeated service usage (Oliver 1999). Customer satisfaction has as overall evaluation of prior performance may become

Figure 2. Customer Retention Process

Customer retention is the most discussed topic in this competitive scenario. Every company is luring the customers of other service providers by various offers, promotional strategies, referrals schemes, discounts. The issue of customer retention in telecommunication industry in Sri Lanka was studied by Silva, K.A (2009). The author found that the most important factor in continuing an existing service provider was the ability of the service provider to give value to the customer. This was followed by assurance and responsiveness.

According to researcher, (Leisen and Vance 2001) better and reliable service quality always helps to create the necessary competitive advantage in a short span of time by being an effective differentiating factor. Service quality was initiated

33

in the 1980s as the worldwide trend in various service and manufacturing firms. The marketers realized that only a quality product could not be guaranteed to maintain competitive advantage (Wal et al., 2002). As per the research conducted by Johnson and Sirikit 2002, service delivery systems in case of mobile services have the ability to allow managers of company to identify the real and correct customer feedback and satisfaction on their telecommunication service so as to retain the customers. The impact of perceived quality on the attitude of the service consumers toward the extension is unambiguously positive. To add to it, both researchers (Omotayo and Joachim 2008) concluded that the relationship between customers’ services on customer retention in telecommunication industry in Nigeria is highly positive. Many researchers put forward that the respondents have a positive impression towards their telecom company’s ability to meet their changing needs.

Consumer choice of mobile service provider is mainly considered to be influenced by different factors like economic condition, convenience of purchasing, efficiency in the operation, and dependability of service or use (Solomon et al. 2003); reference group, life style and social class of the consumer (Turckwell 2004); and attitudes, personality and opinion leadership (Shapiro, 1996). As per the research done by, Kotler and Armstrong 2001 the consumer always perceives price as the total sum of all values that a consumers receives for using the product or service.

Pricing of the services plays a vital role in telecommunication scenario especially for the mobile service providers (Kollmann, 2000). In this era of information age, price competition has become cutthroat in mobile telecommunication industry. Quality mainly reflects the level to which a product or service meets or exceeds customers’ expectations (Wal et al. 2002).

So, the success of mobile sector in the competitive market place significantly depends on product quality and availability of the services. As per Alvarez and Casielles 2005, promotion is a complete set of stimuli which are offered sporadically, and it always reinforces publicity actions so as to promote the purchasing of a certain product or services. This helps the marketers to roll out different promotional strategies to attract new and potential customers in case of any product or service.

Customer retention is directly related to profit making and for that purpose service preference which provides guidelines for service quality and upgradation is important to be considered to maximize service level (Laukkanen, 2007). The most important point for investing in customer retention strategies is that the cost of acquiring new customers compared with the cost of retaining the existing customers. International research by Coopers & Lybrand has shown that it can be at least five times as hard to acquire new customers than to keep existing customers (and sometimes up to 25 times as hard). The objective of a customer retention strategy should be to nurture long-term relationships with customers through trust, responsiveness, customised services and reliability.

III. RESEARCH METHODOLOGYThe main aim of this research study is to figure out the customers’ attitude and perception related to their mobile service provider in Haryana, India. For this, a complete self structured questionnaire was first developed and used to collect the primary data from the consumer of mobile services. The questionnaire consisted of 4 different categories; each section had relevant questions complying with the objective of the research. Both primary and the secondary data collection methods were employed during research. Secondary research was mainly used to study the work done by other fellow researches in the service sector to form the basis of this research.

Non probability convenience sampling technique was adopted to get the primary data from respondents. Likerts’ 5-point scale was used to rate their perception related to various factors like quality of the service, pricing, availability of options, promotional programs, empathy and ethical practices.

A total of 125 sample size was used in the study. Out of this 110 questionnaire were completely and systematically filled and considered for the analysis. Descriptive statistics were also used to compute frequencies and mean scores for the respondents’ profiles or for the other constructs. Factor analysis was used in the research to do analysis of the primary data.

IV. DATA ANALYSIS AND DISCUSSIONThe following research is conducted to figure out various factors which affect the consumer choice while purchasing or using mobile services. The outcomes are very useful for academicians and Mobile service Sector in order to retain the customers and attract the new one. The factors are self explanatory and relevant. The primary data was analyzed in terms of Standard Deviation and Mean Score. Standard deviations were used in order to assess the relative importance of the above discussed factors. The factors were categorized based on their extent of importance on the basis of output produced by Standard Deviation into small extent, moderate extent and high extent. The extent levels are defined as follows:

Figure 3. Customer Loyalty Process.

CUSTOMER SATISFACTION IN CASE OF MOBILE SERVICES

34


a) Small Extent is considered if the Standard Deviation value is (1 < SE < 2.5).

b) Medium Extent is considered if the Standard Deviation value is (2.6 < ME < 3.5)

c) Large Extent is considered if the Standard Deviation value is (3.6 < LE < 5.0)

From the table we conclude that the telecom customers of Haryana state give preference to the network quality or the network coverage, with the mean score value of 4.39: this factors gets the top ranking. Apart from it, the customer care is ranked by the respondents at second place with the mean score of 4.25. The comprehensive outcomes are shown in the table below,

TABLE 1 -- RESPONDENTS, PRIORITIES IN MOBILE SERVICE ATTRIBUTES

Factor Mean score

St. Deviation

Rank

Network Coverage 4.39 0.84 1

Courteous customer service 4.25 4.38 2

Availability of Offers 4.21 0.97 3

Variety of tariffs 4.16 0.93 4

Low Data costs 4.13 2.18 5

Low calling costs 4.11 1.13 6

Decongested network 4.02 1.14 7

Fast Internet Speed 3.73 1.26 8

Price of SIM card 3.71 1.18 9

After sales technical support 3.56 1.24 10

Availability of customer care centres 3.46 1.21 11

Company Advertisement 3.41 1.34 12

Physical Attributes 3.38 1.23 13

Roaming Facility 3.28 1.53 14

Advertisement and promotions 3.23 1.35 15

Corporate Social Responsibility 3.19 1.34 16

Value for Money 3.16 1.27 17

It becomes very clear that the respondents need good and courteous customer care which can help them out in case they face any problem. Other important factors are the availability of good offer be it in terms of recharge, data plans or any other. Data plans i.e. internet plans and the data speed also considered as important aspect while choosing any mobile service provider by the respondents. Now more and more people are buying the smart phones so as to access the internet at very high speed. With the advent of social media and social messenger the demand of smart phones has multiplied many folds not only in urban areas but in rural areas too.

Reliability Coefficient: For any research the reliability is a major issue, and to address this issue Cronbach Alpha (α) is

widely used. The value of the Cronbach alpha should range between 0 and 1. If the value of Cronbach Alpha is higher or near to 1 then the reliability is high and it is a good indicator for the better outcome of research.

TABLE 2 -- RELIABILITY ANALYSISStd.

Mean DeviationService Quality (Alpha = 0.9542)Tangibles 3.32 1.02Reliability 3.25 1.03Responsiveness 3.32 1.04Assurance 3.31 0.98Empathy 3.33 1.02Price (Alpha = 0.9102)Satisfactory Price Charge 3.62 1.34Price does not has impact 3.24 1.32Services are desirable than price 3.38 1.29Price plays vital role 3.59 1.27Product Quality and Availability (Alpha= 0.9320)Product outlets available 2.36 1.26Product outlets are too far 2.48 1.41Product offer best solution to need 2.36 1.29Product offer best technology 2.48 1.36Promotion (Alpha = 0.9141)Attractive promotional offer 3.57 1.21Promotional offer does not attract 3.43 1.36Real need than promotional offer 3.42 1.48

The outcome of the reliability test was positive as the values of the Cronbach alpha are ranging between 0.9102 and 0.9542. The value of the service quality construct is having maximum Cronbach alpha value i.e. 0.9542, and the minimum value of Cronbach 0.9102 that is of price construct. The values are very close to 1, so we can say that study is of considerable importance. All other values are listed above in the reliability analysis table. In the study all the constructs were carefully chosen by doing the pilot survey earlier in Haryana with 60 respondents. The reliability analysis was done with the help of the SPSS Software.

TABLE 3 -- KAISER-MEYER-OLKIN MEASURE OF SAMPLING ADEQUACY

0.942

Bartlett’s test of sphericity Approx. chi-square 1063.963

Df 397

Sig 0

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The constructs validity was tested applying Bartlett’s Test of Sphericity and the Kaiser–Mayer–Olkin (KMO) measure of sampling adequacy analyzing the strength of association among variables. The KMO measure of sampling adequacy was first computed to determine the suitability of using factor analysis. It helps to predict whether data are suitable to perform factor analysis. KMO is used to assess which variables to drop from the model due to multi-collinearity problem.

The value of KMO varies from 0 to 1, and KMO overall should be 0.60 or higher to perform factor analysis. If this does not have achieved, then it is necessary to drop the variables with lowest anti image value until KMO overall rises above 0.60. Result of the Bartlett’s test of sphericity and the KMO revealed that both were highly significant and eventually concluded that these variables was suitable.

Garrett’s ranking technique was used to find out the most significant factor that influences the respondent (Consumers) while choosing their current telecom service provider. In order to calculate the ranking with the help of this Ranking technique, respondents have been asked to assign any suitable rank for all factors that were listed in the questionnaire and the outcome of such ranking were converted into the Mean score value with the help of the following formula:

Percent position = 100 (Rij – 0.5)/ Nj whereRij = Rank given for the ith variable by jth respondents Nj = Number of variable ranked by jth respondents

TABLE 4 -- REASON FOR CHOOSING CURRENT TELECOM OPERATOR

S. No.

Factors GARRETT MEAN SCORE

Ranking

1 Continuous connectivity 49.12 1

2 Call charges 48.14 3

3 Seamless Network 47.28 4

4 Good Internet Speed 48.32 2

5 Provide good service 45.23 7

6 Customer Care 46.65 5

7 Friend Suggestion 45.87 6

8 Promotional Offers 44.66 8

From the Garrett Table, the Mean Score was calculated to know the respondents preference for choosing their current Service Provider. The factors having highest mean value is considered to be the most important factor. As per the respondents answers, it was concluded that the Connectivity plays a vital role in choosing their current service providers over competitors. It means that good connectivity is always the first preference of the mobile users. Here also, the Continuous connectivity

construct with a Mean Score of 49.12 was ranked on top over other valid factors. The consumers also give considerations to the Internet speed for choosing the mobile services of a telecom operator with the Mean Score of 48.32. In our research, call charges and the customer care were also listed in the top 5 rankings of the respondents for choosing a operator or staying with their current service provider. It means that various telecom service providers should take care of the above listed parameters on priority. Otherwise retention of consumers will be very difficult in the era of extreme competition.

TABLE 5 -- CHI-SQUARE TESTSValue df Asymp. Sig.

(2-sided)

Pearson Chi-Square 434.149a 56 .000

Likelihood Ratio 411.241 56 .000

Linear-by-Linear Association 2.269 1 .132

Number of Valid Cases 208

From the chi square test, it may be concluded that the satisfaction from the services of primary service provider is high. As the value of the pearson coefficient is much less than the 0.05 value and because of this, the hypotheses is accepted. As per the hypotheses, the subscribers feel satisfied with their primary service providers be it data provider or mobile service provider or both.

The quality of Service plays a vital role in the case of Telecom Sector. As more and more service providers are foraying into the Indian telecom Arena, this has increased competition level in the Telecom Industry. With the advent of various new smart phones at cheap rates, the telecom industry especially in data sector is providing a lot of data services. More youths are inclined to better data speed and data plans. That’s why the companies are looking to lure the customers by providing them the experience of fast speed at their service points.

The Kruskal-Wallis H test (sometimes also called the “one-way ANOVA on ranks”) is a rank-based nonparametric test that can be used to determine if there are statistically significant differences between two or more groups of an independent variable on a continuous or ordinal dependent variable. As we can notice from the Kruskal Wallis Test that the Service plays a vital role in deciding the selection of the Service provider for telecom purpose. From the above figure, it can be concluded that for customers service quality is very important. The significance of all the factors of service quality (like good network, availability of vas, good knowledge of customer care, good coverage in terms of signals and roaming facility, data speed, availability of better data plans and call drops) is less than the prescribed limit of 0.05. it means all the above mentioned factors are of high significance for the customer point of view and from the service providers’ point of view.


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If there is lapse in the either of the service quality, then the customer will look for other options.

The construct good knowledge is having significance level as 0.004 which is much below the prescribed range of 0.05 so we can assume that the customers are highly influenced by the knowledge of customer care and the hypotheses is rejected that there exist no relationship between the knowledge of customer care and switching intentions. Same is the case of other factors of service quality. The value of Kruskal test for good network coverage is also within the prescribed limit so again we reject the hypotheses that there exist no relationship between the switching intentions and network coverage. It clearly specifies that the customers keep on searching for a good service provider in terms of network coverage. It becomes quite obvious that in case the telecom service provider fails to provide good services then the churning will increase drastically and ultimately the profits and revenue will be slashed down.

V. DISCUSSION AND CONCLUSIONThis research shows that the most significant strategy to maintain customer loyalty and customer retention is the creation and maintenance of long lasting relationships between various telecom service providers and their customers. It was found that if there is a very close relationship with the customers and customer care than it generates a number of benefits including customer retention & customer loyalty. The significance of all the factors of service quality (like good network, availability of vas, good knowledge of customer care, good coverage in terms of signals and roaming facility, data speed, availability of better data plans and call drops) is very high as compared to other factors. In order to maintain a proper relationship, trust between service providers and their customers plays a great role. The service providers need to trust their valuable customers before their customers can feel trust towards them. Good relationship can create switching barriers among customers, which is a type of strategy for keeping customers retained and create loyal customer. This study explains that the satisfied customers always generate a positive word of mouth for their service providers. In order to build a good image and reputation for the service provider the customers must be satisfied fully. It is important for the companies to have good

customer care who can guide the customer whenever they face any sort of problem. Customer care should think about how to behave with the customers and how to treat them. One of the most important factors in the creation of customer satisfaction is that the service provider should provide personal service towards the high usage customers. In the end, the service provider should realize that it is less costly for them to work towards keeping customers loyal than to attract new customer.

VI. SCOPE FOR FUTURE RESEARCHThe study was concentrated mainly on customer retention and customer loyalty. During our study several different other topics that would be interesting to research came up. These are:

1. Research how companies attract new customers.2. Investigate if customer satisfaction really helps in customer

retention. 3. Conduct a study on the customer decision process.4. Conduct a study on how the customer retention programs

differ between large and small companies. 5. Conduct a study on brand loyalty and customer switching

intentions to a specific brand6. Compare customer retention to a specific product or service

with others.

VII. REFERENCES[1]. Stone, M., Woodcock, N. and Machtynger, L. (2000). Customer

Relationship Marketing. London: Kogan Page ltd. [2]. Baker, W., Hutchinson, J.W., Moore, D. and Nedungadi, P.

Brand familiarity and advertising: Effects on the evoked set and brand preferences. Advances in Consumer Research, Volume 13, No.1, pp. 637-643, 1986.

[3]. Fornell, C.. A National Customer Satisfaction Barometer: The Swedish Experience. Journal of Marketing, Volume 56, No.1, pp. 6-22, 1992.

[4]. Kumar, V. and Shah, D. Building and Sustaining Profitable Customer Loyalty for the 21st Century. Journal of Retailing, Volume 80, No. 4, pp. 317-331, 2004.

[5]. Marken, G.A.. It’s Marketing Time: Do You Know Where Your Customers Are? Public Relations, Quarterly Volume 34, No. 4, pp. 23-26, 1990.

[6]. O Malley, L. (1998). can loyalty schemes really build loyalty? Marketing Intelligence and Planning, Volume 16, No. 1, pp. 47-55.

TABLE 6 -- KRUSKAL WALLIS TEST STATISTICSA,B

Service_Quality_Good_Network

Service_Quality_Good_VAS

Service_Quality_Good_Knowledge

Service_Quality_Good_Coverage_Roaming

Service_Quality_Data Speed_Plans

Service_Quality_Success_Calls_SMS_Recharges

Service_Quality_No_Call_Drops

Chi-Square 131.272 112.216 77.221 75.091 57.233 81.325 72.405df 8 8 8 8 8 8 8Asymp. Sig. .040 .003 .004 .023 .025 .021 .031

a. Kruskal Wallis Testb. Grouping Variable: Primary_Service_Provider

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[24]. Kim, B., Shi, M. and Srinivasan, K.“Reward Programs and Tacit Collusion”, Marketing Science, Volume 20, No. 2, pp. 99-120, 2001.

[25]. Gupta, Sunil and Lehmann, Donald. “Managing Customers as Investment, The Strategic Value of Customers in the Long Run.” Wharton School of Publishing, 2005

[26]. Selden, Larry and Colvin, Geoffrey. “Angel Customers & Demon Customers, Discover Which Is Which and Turbo-Charge Your Stock.” Portfolio, 2003.

[27]. Hughes, Arthur Middleton. “Customer Churn Reduction and Retention for Telecoms.” Racom, 2008.

[28]. Chakraborty, S. (2005) Mobile Phones Bridging the Information Divide, Issues and Lessons from Africa. JOMC 223: Global Impact of New Communication Technologies. University of North Carolina at Chapel Hill

[29]. Cronbach, L.J. “Coefficient Alpha and the Internal Structure of Tests”, Psychometrika, Vol. 16, No. 4, pp. 297 – 334, 1951.

[30]. de Silva, H. and Zainudeen, A. Poverty Reduction through Telecom Access at the Bottom of the Pyramid. Centre for Poverty Analysis Annual Symposium on Poverty Research in Sri Lanka, Colombo, December 6 -7, 2007.

[31]. Donner, J., The Use of Mobile Phones by Micro Entrepreneurs in Kigali, Rwanda: Changes to Social and Business Networks. Information Technologies and International Development, Volume 3, No.2, pp. 3-19, 2007.

[32]. Gerstheimer, O. and Lupp, C. Needs versus Technology – The Challenge to Design Third-Generation Mobile Applications. Journal of Business Research, No.12, pp.1409-1415, December 2004.

[33]. Hamel, G. and Prahalad, C.K. Corporate imagination and expeditionary marketing. Harvard Business Review, Volume 69, No.4, pp. 81-92, 1991.

[34]. Hansen, L. (2003). Service Layer Essential For Future Success. Ericsson Mobility World, General article, (June), available at: ttp://www.ericsson.com/mobilityworld/sub/articles/other_articles/nl03jun05

[35]. In-Starts/MDR (2002), ‘The Worldwide PDA Market: The Next Generation Of Mobile Computing’, Research Report (Accessed, January 15, 2015).

Vishal Garg is Research Scholar at Thapar University, Patiala on Consumer Behavior in Telecom Sector. He is working as an Assistant Professor in the Department of Management at Seth Jai Parkash Mukand Lal Institute of Engineering & Technology, Radaur. Teaches courses in Service Marketing, Consumer Behavior, Marketing Research, Marketing Management and Strategic Management. Presented and published several papers. Has good hand on SPSS software in Marketing Sector.

Presented seminars on Entrepreneurship Development Programs and authored books on Service Marketig, Economics and Principles of Management. His qualification includes B.Tech (Computer Science) and MBA (Marketing and Finance). Taught at Lovely Professional University, Jalandhar and Maharishi Markendeshwar University, Mullana.

[7]. Wirtz, J., & Mattila, A.S. (2003). The effects of consumer expertise on evoked set size and service loyalty. Journal of Service Marketing, Volume 17,. No. 7, pp. 649-665.

[8]. Maxam III, JG. & Netemeyer, RG. (2002), “Modeling customer perceptions of complaint handling over time: the effects of perceived justice on satisfaction and intent”, Journal of Retailing, Volume 78, pp. 239-252

[9]. Rao, S. & Jain, D., “A Multi Variant Analysis of Loyalty Programs in Retail Store in Delhi”, Advances in Management, Volume 2, No. 2, pp. 54-59, 2009.

[10]. Strauss, B., Schmidt, M. and Schoeler, A., “Customer frustration in loyalty programs”, International Journal of Service Industry Management, Volume 16, No. 3, pp. 229-252, 2005.

[11]. Zeithaml, VA., Berry, LL. and Parasuraman, A., “The Behavioral Consequences of Service Quality”, Journal of Marketing, Volume 60, No. 2, pp. 31-46, 1996.

[12]. Liu, Y., “The Long-Term Impact Of Loyalty Programs On Consumer Purchase Behavior And Loyalty”, Journal of Marketing, Volume 71, No. 4, pp. 19-35, 2007.

[13]. Reinchheld, FF., The Loyalty Effect: The Hidden Force Behind Growth, Profits And Lasting Value, (pp. 909), Harvard Business School Press Books, Boston, 1996.

[14]. Turner, JJ. & Wilson, K., “Grocery loyalty: Tesco Clubcard and its Impact on Loyalty”, British Food Journal, Volume 108, No. 11, pp. 958-964, 2006.

[15]. Jang, D. & Mattila, AS., “An Examination Of Restaurant Loyalty Programs: What Kinds Of Rewards Do Customers Prefer?” International Journal of Contemporary Hospitality Management, Volume 17, No. 5, pp. 402-408, 2005.

[16]. Boshoff, C., “RECOVSAT: An instrument to measure satisfaction with transaction specific service recovery”, Journal of Service Research, Volume 1, No. 3, pp. 236-24,1999.

[17]. Duffy, DL. “Internal and External Factors which Affect Customer Loyalty”, Journal of Consumer Marketing, Volume 20, No. 5, pp. 480-485, 2003.

[18]. Oliver, RL., “A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions”, Journal of Marketing Research, Volume 17, No. 4, pp. 460-469, 1980.

[19]. Noordhoff, C., Pauwels, P. and Oderkerken- Shroder, G., “The Effect of Customer Card Programs: A Comparative Study in Singapore and the Netherlands”, International Journal of Service Industry Management, Volume 15, No. 4, pp. 351-364, 2004.

[20]. Mittal, V., Ross, W.T., & Baldasare, P.M. The Asymmetric Impact of Negative and Positive Attribute-Level Performance on Overall Satisfaction and Repurchase Intentions. Journal of Marketing, Volume 62, No.1, pp.33-47, 1998..

[21]. Ping, R.A., The Effects Of Satisfaction And Structural Constraints On Retailer Exiting, Voice, Loyalty, Opportunism, And Neglect. Journal of Retailing, Volume 69, No. 3, pp. 320-353, 1993.

[22]. Singh, J., and Sirdeshmukh, D. Agency and Trust Mechanisms in Customer Satisfaction and Loyalty Judgements. Journal of the Academy of Marketing Science, Volume 28, No. 1, pp. 150-156, 2000.

[23]. O’Malley, L., “Can Loyalty Schemes Really Build Loyalty?”Marketing Intelligence & Planning, Volume 16, No. 1, pp. 47-55, 1998.


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Design Optimization of IC Engine Rocker-arm Using Taguchi Based Design of Experiments

Dr. Goteti Chaitanya1 and Reddy Sreenivasulu2

Department of Mechanical Engineering, R.V.R and J.C. College of Engineering, Chandramoulipuram, Chowdavaram, Guntur 522 019 Andhra Pradesh

[email protected], [email protected]

Abstract — During the past decades, rocker arms have been optimized for delivering better performance. Fatigue life, durability, toughness, high dimension stability, wear resistance, strength as well as economic factors influenced the selection of criteria for optimization. Rocker arms are mainly subjected to cyclic loads and their fatigue life plays a vital role in their design. Therefore, this work aims at designing the rocker arm for higher fatigue life by changing material and arm ratio. Three different materials and three different arm ratios are chosen as inputs.

The rocker arm is modeled using CATIA V5 software and the fatigue analysis is carried out using ANSYS 14.5 APDL finite element software. The total deformation, Vonmises equivalent stresses, factor safety are evaluated for each combination. Taguchi based design of experiments is applied and the trials are conducted using L9 orthogonal array. From the design of experiments, it is observed that structural steel having arm ratio of 1:1 provides the best combination for higher fatigue life.

Keywords: Rocker arm, Arm ratio, Fatigue life, Orthogonal array.

I. INTRODUCTIONROCKER arm is an important part of the valve train in fuel injection system providing not only the means of actuating the valves through a fulcrum utilizing the lifter and the push rod but also provide a means of multiplying the lift ratio. Cam shaft design advanced in leaps and bounds over last three decades but overhead valve engines with centrally located camshafts still use lifters and push rod and rocker arms as a means of opening and closing the intake and exhaust valves in fuel injection pumps. Advancements in materials used in construction of rocker arm for reducing noise, weight and improving strength for efficient operation are going on throughout the globe since long. The usual materials used for such purpose are Steel, Aluminum, and Forged steel to Stainless steel, aluminum alloys and composites. The success lies in investigating the possibility of creating a light weight rocker arm which provides higher fatigue life, reduced friction between the rocker and the valve stem but still remain economical. Structural and mechanical components subjected to fluctuating service stress (or more appropriately, strain) are susceptible to failure due to fatigue.

A. Nagaraja and G. Suresh Babu [1] made an effort to design a rocker arm for a four wheeler using theoretical formulas. In this theoretical calculation is done for design for fulcrum pin, Design for forked end, Design for rocker arm cross-section, Design for Tappet, and Design for valve spring. Syed Mujahid Husain and Siraj Sheikh [2] reviewed the various types of rocker arms, based on published sources from the last 40 years in order to understand rocker arm for its problem identification and further optimization. Mohd Moesli et al. [3] presented the failure analysis of a diesel engine rocker arm, used in shipsand boats, which failed in service. The fracture occurred at the threaded part of the rocker arm. A detailed metallurgical investigation was conducted to indentify themode of failure and the point at which the crack was initiated. Lenin Rakesh N. and A. Thirugnanam [4] carried out finite element analysis to find out the stress analysis of rocker arm and the hand crank and compared results with experimental test procedures to validate the magnitude, position and frequency of occurrence of various failure modes.

Antaryami Mishra [5] made an attempt to find out various stresses under extreme load condition for a polymer matrix composite rocker arm. Glass fibre reinforced (10% volume fraction) High Density Polyethylene (HDPE) composite rocker arm of fuel injection pump has been considered for analysis owing to its light weight, higher strength and good frictional characteristics. Christer Spiegelberg and Soren Andersson [6] presented that the surface velocities obtained from a rigid body model are used to simulate friction and wear in the contact between the rocker arm pad and valve bridge in the cam mechanism of a diesel engine.

The friction is simulated with two different friction models, a 3D brush model capable of handling transient conditions such as an varying normal load and varying surface velocities and a Columbian friction model. Chin-Sung Chung and Ho-Kyung Kim [7] presented a paper on rocker arm in 2005.In order to evaluate the fatigue endurance for the rocker arm of a diesel engine, stress measurements were performed using strain gages attached near the neck, which is one of the most critical regions

39

in the rocker arm, while varying the engine speed. Fatigue life experiments were carried out on miniature specimens taken from rocker arms. To evaluate the fatigue endurance of the rocker arm, the S–N data were compared with the stress analysis results obtained through a Finite Element Modeling (FEM) analysis of the rocker arm. Dong Woo Lee, Seok Swoo Cho and Won Sik Joo [8] presented the failure analysis of a rocker arm shaft for a 4-cylinder SOHC engine.

Fractures occurred at the interface between the rocker arm shaft and the engine block. These fractures were found to be responsible for bolt tightening. Srinivasa Athreya [9] applied the Taguchi based optimization technique for lathe process parameter optimization in order to improve the surface finish. Messias Borges Silva et al. [10] Presented the Taguchi Method, a statistical design modeling for experiments applied in Environmental engineering. This method was applied to optimize the treatment conditions of polyester-resin effluent by means of Advanced Oxidative Processes (AOPs) using chemical oxygen demand (COD) as response parameter. The influence of each independent parameter including respective interactions was evaluated by Taguchi Method, which allowed determining the most statistically significant variables and conditions to best fit the process. Balla Yuvaraj et al. [11] Presented the Taguchi design of experiments and orthogonal array to find a specific range and combinations of turning parameters like cutting speed ,feed rate and depth of cut to achieve optimal values of response variables like surface finish, tool wear, material removal rate in turning of Brake drum of FG 260 gray cast iron Material. In this work, the rocker arm is modeled using three different materials namely Aluminum composite, AL6061 alloy and structural steel. Three different arm ratios i.e. 1:1, 1:1.15 and 1:3 were chosen for analysis based on available literature. The finite element model was made using structural solid 187 element. A completely reversed bending load of magnitude 1900 N chosen from TAPEQRS-Truck rocker arm is applied on the finite element model of rocker arm. Structural steel with arm ratio of 1:1 showed to have highest fatigue life of 17983 cycles.

II. MODELING AND FINITE ELEMENT ANALYSISFigure 1 shows the CATIA V5 models of rocker arm and its pin assembly. The finite element model

Of the rocker arm using structural solid 187 is shown in fig2. A medium mesh (Neither too coarse nor too fine) is used for the analysis. Tables 1 to 3 display the properties of Aluminum composite, structural steel and AL6061 alloy. Ansys uses Good Man’s mean stress theory to determine the fatigue life.

TABLE 1 -- PROPERTIES OF ALUMINUM COMPOSITES. No. Mechanical Properties Value Units

1 Density 2.77 g/cm3

2 Ultimate tensile strength 331.24 MPa3 Modulus of elasticity 90.67 GPa4 Poisons ratio 0.33 ----5 Tensile yield strength 284.49 MPa6 Shear strength 215 MPa

TABLE 2 -- PROPERTIES OF STRUCTURAL STEELS. No. Mechanical Properties Value Units

1 Density 7.85 g/cm3

2 Ultimate tensile strength 460 MPa3 Modulus of elasticity 200 GPa4 Poisons ratio 0.30 ----5 Tensile yield strength 250 MPa6 Shear strength 345 MPa

TABLE 3 - PROPERTIES OF Al-6061S. No. Mechanical properties Value Units

1 Density 2.7 g/cm3

2 Ultimate tensile strength 310 MPa3 Modulus of elasticity 68.9 GPa4 Poisons ratio 0.33 -----5 Tensile yield strength 276 MPa6 Shear strength 207 MPa

III. FINITE ELEMENT ANALYSIS RESULTSOut of the three material combinations chosen for different arm ratios, rocker arm made of structural steel with arm ratio 1:1 displayed highest fatigue life, least total deformation was shown by AL 6061 alloy with arm ratio 1:1.3, and least Vonmises

Figure 1. Rocker arm and pin assembly.

Figure 2. FEM Model of rocker arm.

DESIGN OPTIMIZATION OF IC ENGINE ROCKER-ARM

40


and used in determination of optimal combinations of input parameters i.e., material as well as arm ratio for each of the output parameters using Taguchi methods. Minitab 17 is used for Taguchi experimental design with L9 orthogonal array. The plots for signal to noise ratio for fatigue life, total deformation, and Vonmises stresses are plotted. The criteria for each output parameter are shown in Table 5.

Figure 6 shows the signal-to-noise ratio for minimum life. Since the minimum life has to be maximum the larger the better criteria is considered. It can be concluded that the material at level 1 and Arm Ratio at level 1 i.e. structural steel with 1:1 Arm Ratio will give maximum life than the remaining combinations. Figure 7 shows the signal-to-noise ratio for equivalent stresses .Since the equivalent stresses has to be minimum the smaller the better criteria is considered. It can be concluded that the material at level 3 and Arm Ratio at level 3, i.e. Aluminum composite with 1:1.3 Arm Ratio will give minimum than the remaining combinations.

Figure 8 shows the signal-to-noise ratio for minimum deformation .Since the minimum deformation has to be

Figure 3. Total deformation (steel)

Figure 4. Vonmises stress (steel)

Figure 5. Minimum finite Fatigue life of structural steel in cycles.

TABLE 4 -- STRUCTURAL FATIGUE ANALYSIS RESULTSMaterial Arm ratio Total deformation (mm) Equivalent Stress(MPa) Fatigue Life (cycles) Safety Factor

Structural 1:1 0.035 220.74 17983 2.96

Steel

Structural 1:1.15 0.044 240.06 13492 2.72

Steel

Structural Steel 1:1.3 0.057 253.5 11197 2.58

Al composite 1:1 0.10017 221.55 14977 2.83

Al composite 1:1.15 0.125 242.72 5151.6 2.61

Al composite 1:1.3 0.16222 253.87 3374.9 2.47

Al 6061/ 1:1 0.0784 221.55 13775 4.8

Al 6061/ 1:1.15 0.09823 242.72 12857 4.42

Al 6061/ 1:1.3 0.127 253.87 8236.3 4.19

equivalent stress was shown by AL composite with arm ratio 1:1.3. The results are shown in figures 3 to 5.

Table 4 displays the overall structural analysis results for different materials and arm ratios.

IV. DESIGN OF EXPERIMENTSResults from the trials conducted using ANSYS are taken

41

i.e. Aluminum alloy with 1:1.3 Arm Ratio will give minimum deformation than the remaining combinations.

V. CONCLUSIONThe following important conclusions are drawn out of the work carried out.

l It can be concluded that the fatigue life of the rocker arm is influenced by the arm ratio and material of rocker arm with it is made .Using Taguchi method, the optimal combination for maximum fatigue life is for rocker made with structural steel and arm ratio 1:1.

l The total deformation is minimum in the case of material AL 6061 with arm ratio 1:1.3.

l The Vonmises stresses are minimum for Al composite with arm ratio 1:1.3.

VI. REFERENCES[1]. A. Nagaraja and G. Suresh Babu “Design and Optimization of

Four Wheeler Rocker Arm for Neck and Hole”, International Journal & Magazine of Engineering, Technology, Management and Research, Volume 2, No. 7, pp. 1296-1305, July 2015.

[2]. Syed Mujahid Husain and Prof. Siraj Sheikh “Rocker Arm: A Review”, International Journal of Innovative Research in Science, Engineering and Technology, Volume 2, No.4, pp. 464-473, April 2013.

[3]. Mohd Moesli, Muhammad Syed Rosli ,Sayd Bakar and Irwan Mohd Noor, “Failure Analysis Of A Diesel Engine Rocker Arm,” Defense Science and Technology Technical Bulletin, Volume 13, No. 4, pp. 598 – 605, June 2006.

[4]. N. Lenin Rakesh and A. Thirugnanam, “Stress Analysis of Hand Crank and Rocker ARM”, Middle-East Journal of Scientific Research, IDOSI Publications, Volume 12, No. 12, pp.1687-1689, 2012.

[5]. Antaryami Mishra, “Stress Analysis of Glass/HDPE Composite Rocker Arm by Finite Element Method”, International Journal of Engineering Science and Innovative Technology, Volume 3, No. 3, May 2014.

[6]. Christer Spiegelberg and Soren Andersson, “Simulation of friction and wear in the contact between the valve bridge and rocker arm pad in a cam mechanism” Machine Design, Royal Institute of Technology, S-100 44 Stockholm, Sweden, pp. 58–67, 2005.

[7]. Chin-Sung Chung and Ho-Kyung Kim, “Safety Evaluation of the Rocker Arm of a Diesel Engine”, Journal of Materials and Design, Volume 31, pp.940-945, 2010.

[8]. Dong Woo Lee, Seok Swoo Cho and Won Sik Joo, “An Estimation of Failure Stress Condition in Rocker Arm Shaft through FEA and Microscopic Fractography” Journal of Mechanical Science and Technology, Volume 22, 2008, pp. 2056-2061.

[9]. Srinivas Athreya and Y.D. Venkatesh, “Application of Taguchi Method for Optimization of Process Parameters in Improving the Surface Roughness of Lathe Facing Operation”, International Refereed Journal of Engineering and Science, Volume 1, No. 3, pp.13-19, November 2012.

TABLE 5 -- CRITERIA OF SELECTIONS. No. Out-parameter Criterion1 fatigue Life Larger the best2 Total deformation Smaller the best3 Vonmises stress Smaller the best

Figure 6: Main effects plot for fatigue life.

Figure 7: Main Effects plot for Equivalent Vonmises stress.

Figure 8: Main Effects plot for total deformation.

minimum the smaller the better criteria is considered. It can be concluded that the material at level 2 and Arm Ratio at level 3,

DESIGN OPTIMIZATION OF IC ENGINE ROCKER-ARM

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[10]. Messias Borges Silva, Livia Melo Carneiro, João Paulo Alves Silva, Ivy dos Santos Oliveira1, Hélcio José Izário Filho and Carlos Roberto de Oliveira Almeida, “An Application of the Taguchi Method (Robust Design) to Environmental Engineering: Evaluating Advanced Oxidative Processes in Polyester-Resin Wastewater Treatment”, American Journal of Analytical Chemistry, Volume 5, pp.828-837, 2014.

[11]. Ballal Yuvaraj P, Inamdar K.H and Patil P.V, “ Application Of Taguchi Method For Design Of Experiments In Turning Gray Cast Iron”, International Journal of Engineering Research and Applications, Volume 2, No. 3, pp.1391-1397, May-Jun 2012.

Dr. G. Chaitanya received his M E degree from Satyabhama University, Chennai and PhD degree from JNTU, Hyderabad. He has published over 10 articles in international journals and presented over 2 articles at different national conferences. Currently Dr. G.Chaitanya is an associate professor in the department of Mechanical Engineering, R.V.R & J.C College of Engineering (Autonomous) Guntur, Andhra Pradesh, India. He is life member of ISTE and IAENG.

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Latest Trends in CommunicationsManjit Singh, FIETE

B 54, Sector 15, Noida 201301 UP [email protected]

Abstract — If humans are the only internet users of the future, then the total user base might conceivably double, but is unlikely to go beyond two billion active users in the near future. On the other hand, if “things” become active internet users on behalf of humans, then the number of active connections could be measured in terms of tens or hundreds of billions.

The internet and other data transmission services (e.g. SMS, MMS), initially the purview of the developed world, are also gaining market share in developing economies, boosting information and communication access and increasing demand for bandwidth.

With Internet of things, it is expected that there will be 300 billion things connected to network by 2025. There will be Tsunami of data to meet the demands of internet of things and other smart phone applications.

Keywords: Internet, IOT, 5G, New Generation Networks, Software Defined Radio, Smart Cities, Digital India

INTERNET began in the late 1960s as a link between a handful of university computer centers. In the 1970s and 1980s, the use of the Internet was dominated by e-mail and file transfer, and the number of users was counted in thousands. In the 1990s, web browsing became dominant and users were denominated in millions. The Internet as we know it today will radically change over the next decade. As of the end of 2015, there were some 3.36 billion internet users worldwide. Moreover, mobile phones, of which there were over 2 billion at the end of 2015, are being used more and more as devices for internet access. This creates new applications and services hitherto unknown, through both 2G systems and a growing subscriber base for IMT-2000 (3G) systems.

The internet and other data transmission services (e.g. SMS, MMS), initially the purview of the developed world, are also gaining market share in developing economies, boosting information and communication access and increasing demand for bandwidth. Today, we are heading into a new era of ubiquity, where the “users” of the internet will be counted in billions and where humans may become the minority as generators and receivers of traffic Instead, most of the traffic will flow between devices and all kinds of “things”, thereby creating a much wider and more complex “Internet of Things”.

If humans are the only internet users of the future, then the total user base cited above might conceivably double, but is unlikely to go beyond two billion active users in the near future. On the other hand, if “things” become active internet users on behalf of humans, then the number of active connections could be measured in terms of tens or hundreds of billions.

I. INTRODUCTIONTHE TRENDs in Communications can be classified into three parts:l Trends in Communications technologiesl Trends in Data management andl Trends in Operators perspective to meet the challenges with

minimum costs and manage the networks efficiently.

First we will take up the communication technologies. As we all know the communication can be People to people: This has been the trend since the civilization started as people were communicating with each other with different mans of communications.

In the present day technological world, the simple and universal set of network can be represented as in Figure 2.

As we can see there is a central office Next Generation Networks (NGN) which has different types of connections depending upon the network voice, data fibre etc. All the connections are part of access technologies.

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II. ACCESS TECHNOLOGIESIn people-to- people communication, the speech is transmitted through the network called Access Network. There have been fixed phones, which are location based and were identified by the address or place where the phone is installed. In seventies came the wireless technology that was analogue as below:

l TACS: Total Access communication system. This was working in UK in the frequency band 890-915 MHz and 935-960 MHz

l NMT Nordic Mobile Telephone (Europe) This was developed in the frequency band of 453-457.5 MHz and 953-960 MHZ

l AMPS: Advanced Mobile Phone System 824-849 MHz and 869-894 MHz.

All these technologies being analogue, there were difficulties of capacity and quality of speech and interference issues.

This was First generation of mobile system called 1st Generation.

2nd Generation: To overcome many of the issues, European countries (ETSI) joined hands and started to develop a digital system. Many European companies like Nokia, Alcatel and Ericsson were given the task of development while the specification was being developed. This was called Groupe Speciale Mobile GSM System. It is based on TDMA technology (Time division Multiple Access)and started its operations in 1988-90 time frame.

In USA, Qualcomm was trying to develop second generation digital CDMA system (Code Division Multiple Access). The CDMA was developed in Freq. band 824-869 MHz while GSM was developed in 890-915 and 935-960 MHz and the 1710-1785 and 1805-1880 MHz to meet capacity demand.

Many countries chose the GSM technology and this made the roaming between these countries feasible. The demand

for CDMA 2G technology could not reach many countries basically due to delay in its development and cost issues. The CDMA technology was owned by Qualcomm and was not open standards as the GSM technology.

Therefore, India also adopted GSM technology. It came to be known as Global System for Mobile Communications (GSM).

(Source TRAI)

In Nineties, the internet and TCP IP technology was so popular resulting in multifold increase in Data because people were using data for emails and transfer of large files. Therefore, the need for data was felt and industry started working on providing data on existing 2G networks. ITU also started working on drawing specifications called IMT 2000. This development was started in 2000 and called 3G technology. In the meantime to meet immediate need for data EDGE (Enhanced datarates for GSM evolution) was developed to give data speed of 144 kbps and it was called 2.5G ( This name was given by industry) to distinguish from 2G and 3G.

ITU standardized the 3G technology based on CDMA as it was considered to be spectrum efficient and more secured. Since majority of networks were working on GSM 2G technology, a 3GPP (Third generation Partnership group) was formed to develop specification for system called UMTS ( Universal Mobile Telecom System). The technology recommended was called WCDMA (Wideband CDMA).

Qualcom also started working on CDMA 2000 to meet the ITU Spec. In its wisdom ITU developed specification and made it technology neutral. The data speeds in 3G are 2 Mbps.

As need for data increased, the speed as given by 3G technology was found slow. The need for next generation was felt and it is called 4G technologies. 4G technology was also termed as Long Term Evolution and a speed of 100 Mbps was specified. 3GPP group was working on the technology and in 2010 this came into existence. 4G take into account data packaging and is an all IP technology.

To meet the need for higher BW the freq. range for 4G technology is 2.5 GHz. From 2005-2010 the industry worked

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We can see that a new mobile generation has appeared approximately every 10th year since the first 1G system, Nordic Mobile Telephone, was introduced in 1981. The first 2G system started to roll out in 1991, the first 3G system first appeared in 2001 and 4G systems fully compliant with IMT Advanced were standardized in 2012. The development of the 2G (GSM) and 3G (IMT-2000 and UMTS) standards took about 10 years from the official start of the R&D projects, and development of 4G systems started in 2001 or 2002.

The proliferation of video streaming and other social media is making even 4G slower and the development of next generation of wireless access networks are being designed. The 5G will give speeds as high as 1GB /sec.

5G will spearhead the use of cognitive radio techniques to allow the infrastructure to automatically decide about the type of channel to be offered, differentiate between mobile and fixed objects, and adapt to conditions at a given time. In other words, 5G networks will be able to serve the industrial Internet and Facebook apps at the same time.

Wireless communication algorithms are implemented using a wide spectrum of building blocks such as: source coding; channel coding; modulation; multiplexing in time, frequency and code domains; channel estimation; time and frequency domainsynchronization and equalization; pre-distortion;

transmit and receive diversity; combat and take advantage of fading and multi-path channels; intermediate frequency (IF) processing in software defined radio, etc.

Major design objectives for future Networksl Implementation of massive capacity and massive

connectivity l Support for an increasingly diverse set of services,

applications and users all with extremely diverging requirements

l Flexible and efficient use of all available non-contiguous spectrum for wildly different network deployment scenarios

l Multiple access and advanced waveform technologies combined with coding and modulation algorithms

l Interference management l Access protocols l Power needs of terminals and equipment-Economizing

Power.l Service delivery architecture l Mass-scale MIMO l Single frequency full duplex radio technologies l 5G devices l Virtualized and cloud-based radio access infrastructure l An adaptive network solution framework will become a

necessity for accommodating both LTE and air interface evolution;

l Cloud, Software Defined Network (SDN) and Network Function Virtualization (NFV) technologies will reshape the entire mobile ecosystem;

l and 5G will speed up the creation of massive-scale services and applications.

III. 5G NETWORKSGeneral industry expectations are for the first 5G services to go live around 2020.

SK Telecom South Korea has announced the use of 5G technology in their network in 2018 during Winter Olympics.

While it’s quite possible that some of the technology, which will comprise the 5G standard, will be found in commercial services that soon, it’s unlikely to be formally called 5G as the final ratification of the standard is unlikely to have happened by then. Of course that won’t stop the marketing people jumping on the bandwagon and the term ‘pre-5G’ is already being used liberally.

One of the main reasons for this is the wide array of technologies that are already being positioned as likely contributors to the eventual standard. There will be two features worth mentioning for successful implementation of 5G technology. One of them is spectral efficiency and the other being capacity to meet the anticipated growth of the Internet of Things (IoT) consequently increase in traffic.

on pre4 G called as 3.5 G and technology called HSPA( High Speed Packet Access) was developed.

4G technology is developed on OFDMA (orthogonal Freq. Division Multiple access) and for antenna it is based on MIMO (Multiple input and multiple output).

The tree below gives growth of 1G to 4G technologies

Figure 3. Evolution of Wireless Technology.

LATEST TRENDS IN COMMUNICATIONS

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Another interesting feature required is the support of NFV/SDN, SON, unlicensed spectrum and full duplexing. In other words 5G is going to be the product of a large number of technologies, but at its core it needs to solve the problem of carrying an enormous traffic.

The move to an all IP mobile environment is likely to remove communication barriers,both geographical and technological. The technology will support borderlessmobility services enabled by an all IP mobile environment.

It will enable seamless mobilevoice and data communication services between mobile networks and Wi-Fi serviceproviders internationally”. The spread of VoLTE will ensure subscribers never have to leave an IP network while using their devices, which in turn opens up a number of new opportunities for dynamic switching between cellular andWi-Fi.

The road to 5G will be a long one, but there’s no question we’re already on it. While the consensus is for commercial 5G services not to appear until 2020 or later, claimed ‘pre-5G’ technologies are already being developed and marketing professionals across the telecoms industry are keen for their brands to be associated with 5G today.

Many of the challenges faced by previous generations of mobile technology need to be confronted once more, such as standardization, cost of roll-out and consumer education. But the potential rewards are greater than ever as more people and devices are set to do more things over more networks. Commerce is set to be increasingly defined by mobile technology so pretty much everyone has a stake in the development of 5G.

Recently, voice over LTE, or VoLTE, has become tantamount to being the future of voice for operators, as well as a potential bastion for securing revenues from what has become a hemorrhaging revenue stream for operators. Voice services as a meaningful source of income have been losing relevance to operators, for the best part, as a new generation of tech-savvy users lean increasingly towards over-the-top instant messaging platforms, coupled with a publicperception of unreliability and poor quality of service being offered up by traditional circuit switched voice systems.

While data networks have, deservedly, received countless upgrades and technological advancements in recent years, unsurprising considering the proliferation and monetization opportunities of data services over the past few years; voice services seem to have slowly died a death, and haven’t received an upgrade or overhaul of note for a decade or more, since UMTS and GSM. VoLTE could well present an opportunity

for operators tomake voice an opportunity for monetization once again for mobile.

IV. MOBILITY AND NGNAt present, the underlying mobility of services remains limited: end-user services other than voice are hardlyportable across networks. This functionality is central to exploiting thing-to-thing communications. In thisrespect, next-generation networks hope to offer mobility much more broadly. “Generalized mobility” isa term closely associated with NGN. It denotes the possibility of seamless and ubiquitous access to services, irrespective of location and the technology used.

NGN is a broad concept, and there are several definitions of NGN at this time. ITU formally defines NGN asa “packet-based network able to provide telecommunication services and make use of multiple broadbandtransport technologies in which service-related functions are independent from underlying transport-related technologies”. In general, most analysts describe NGN as a multi-service network based on Internet Protocol (IP) technology. The fundamental difference between the networks of today and NGN will be the full transition they imply from current circuit-switched networks to packet-based systems such as those using IP (Table 1). A number of network operators havealready begun replacing their Public Switched Telephone Network (PSTN) equipment with next-generationEquipment.

TABLE 1 -- CONTRASTS BETWEEN TODAY’S PSTN NETWORK AND TOMORROW’S NGN

Today’s PSTN network Next-generation Networks

Circuit-switched. Packet-based, based on Internet Protocol (IP).

Limited mobility of end-user services.

Broad-based ‘generalized mobility’.

Vertical integration of application and call control layers, with dedicated networks.

Horizontally-integrated control layers, with simultaneous delivery of applications. Service-related functions independent of transport-related technologies.

V. SMART PHONESAll the benefits of Social networking smart cities, e-governance etc. are only possible due to development of Smart phones with touch technology. The man behind the touch phone technology implementation in phones id Steve Jobs who was CEO of Apple Inc.

His prediction has revolutionized the world with smart phone being made available and its proliferation. Apps on phones and killer applications are helping citizens to fully exploit the use of smart phones.

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All these developments are increasing the load on bandwidth. With Internet of things, it is expected that there will be 300 billion things connected to network by 2025. There will be Tsunami of data to meet the demands of internet of things and other smart phone applications. There will be need for newer technologies to meet the demand of huge data and already 6G and 7 G technologies are being talked. The 6G and 7 G will integrate satellites into the access networks making whole world a real Global village.

VI. INTERNET OF THINGSThere is large demand arising for automation of all processes and machines talking to machines. Even today e-commerce, is M@M communication. The machines will become things . Anything will be connected to internet.

The Data needs of Internet of things:

The IoT is the network of dedicated physical objects (things) that contain embedded technology to sense or interact with their internal state or external environment. The IoT comprises an ecosystem that includes things, communication, applications and data analysis. (Kevin Ashton first used the term Internet of Things in 1999. Refers to uniquely identifiable objects (things) and their virtual representations in an Internet-like structure)

VII. TRENDS IN DATAThe figure below shows the data generated on internet in 60 seconds. DATA Storage is very complex, and indeed, not only does it entail managing capacity and figuring out the best collection and retrieval methods, it also means synching with both the IT and the business teams and paying attention to complex security and privacy issues.

Cyber Securityl Everything connected to Internet is vulnerable: Retailers,

Banks, Technology companies are getting hacked.l Needs Better Cyber security: Techniques beyond current

Firewall-like defensesl Better encryption, Authentication Schemes.

Customers are becoming wary of Data Secrecy and security issues.

VII. TRENDS IN INDUSTRYThe industry has to implement all these developments in the technology to meet the needs and aspirations of its customers. All these implementations will involve huge investments. The operators have to decrease capital costs and, therefore Self Organizing networks (SON) are being implemented

l A self-organizing Network (SON) is an automation technology designed to make the planning, configuration, management, optimization and healing of mobile radio access networks simpler and faster.

l Self Configurationl Self Healingl Self Optimisationl Operators benefit from significant improvements in terms

of both CAPEX, and later OPEX.

The operators are not going to build huge data storage systems as it involves lots of space , power and investments. Therefore Cloud Technology is helping these operators. In addtion to self Organising networks, the operators are also implementing the newer methods of network maintenance by utilising SDN (Software Defined Networks and NFV (Network Functions Virtualisation). SDN allows network administrators to manage network services through abstraction of lower level functionality. This is done by decoupling the system that makes decisions about where traffic is sent (the control plane) from the underlying systems that forward traffic to the selected


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destination (the data plane). The inventors and vendors of these systems claim that this simplifies networking.

SDN requires some method for the control plane to communicate with the data plane. One such mechanism, OpenFlow, is often misunderstood to be equivalent to SDN, but other mechanisms could also fit into the concept. The Open Networking Foundation was founded to promote SDN and OpenFlow, marketing the use of the term cloud computing before it became popular.

The controller acts as an interface between the physical network and the SDN layer. As elastic cloud architectures and dynamic resource allocation evolve and as mobile computer operating systems and virtual machines usage grows, the need has arisen for an additional layer of software-defined networking (SDN). Such a layer allows network operators to specify network services, without coupling these specifications with network interfaces. This enables entities to move between interfaces without changing identities or violating specifications. It can also simplify network operations, where global definitions per identity do not have to be matched to each and every interface location. Such a layer can also reset some of the complexity build-up in network elements by decoupling identity and flow-specific control logic from basic topology-based forwarding, bridging, and routing.

In recent years, user expectations for “anywhere, anytime” access to business and entertainment applications and services are changing the service model needed by carrier network operators. For example, e-commerce applications are now adopting cloud technologies, as service providers continue incorporating new business applications into their service models. For entertainment, video streaming content now includes not only traditional movies and shows, but also user-created content and Internet video. The video delivery mechanism is evolving, as well, to include streaming onto a variety of fixed and mobile platforms. Feature-rich mobile devices now serve as e-commerce and entertainment platforms in addition to their traditional role as communication devices, fueling deployment of new applications, such as mobile TV, online gaming, Web 2.0 and personalized video.

To remain profitable, carriers need to offer value-added services that increase the average revenue per user (ARPU), and to create these new services cost-effectively, they need to leverage the existing datacenter and network infrastructures. This is why the datacenters running these new services are becoming as critical as the networks delivering them when it comes to providing profitable services to subscribers.

Datacenter and carrier networks are quite different in their architectures and operational models, which can make unifying them potentially complex and costly. According to The Yankee Group, about 30 percent of the total operating expenditures (OpEx) of a service providers are due to network costs, as shown in Figure above. To reduce OpEx and, over time, capital expenditures (CapEx), service providers are being pushed to find solutions that enable them to leverage a more unified datacenter-carrier network model as a means to optimize their network and improve overall resource utilization.

Virtualization of the network infrastructure is one strategy for achieving this cost-effectively. Virtualization is a proven technique that has been widely adopted in enterprise IT based on its ability to improve utilization and operational efficiency of datacenter server, storage and network resources. By extending the virtualization principles into the various segments of a carrier network, a unified datacenter-carrier network can be fully virtualized — end-to-end and top-to-bottom — making it far more scalable, adaptable and affordable than ever before.

Leveraging the virtualized datacenter model to virtualize the carrier network has several benefits that can help address the challenges associated with a growing subscriber base and more demanding performance expectations, while simultaneously reducing CapEx and OpEx. The approach also enables carriers to seamlessly integrate new services for businesses and consumers, such as Software-as-a-Service (SaaS) or video acceleration. Google, Facebook and Amazon, for example, now use integrated datacenter models to store and analyze Big Data. Integration makes it possible to leverage datacenter virtualization architectures, such as multi-tenant compute or content delivery networks, to scale or deploy new services without requiring expensive hardware upgrades.

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Incorporating the datacenter model can also enable a carrier to centralize its billing support system (BSS) and operation support system (OSS) stacks, thereby doing away with distributed, heterogeneous network elements and consolidating them to centralized servers. And by using commodity servers instead of proprietary network elements, carriers are able to further reduce both CapEx and OpEx.

Another trend in virtualized datacenters is the abstraction being made possible with software-defined networking, which is enabling datacenter networks to become more manageable and more open to innovation. SDN shifts the network paradigm by decoupling or abstracting the physical topology to present a logical or virtual view of the network. SDN technology is particularly applicable to carrier networks, which usually consist of disparate network segments based on heterogeneous hardware platforms.

NFV is an initiative being driven by network operators with a goal to reduce end-to-end network expenditures by applying virtualization techniques to telecom infrastructures. Like SDN, NFV decouples network functions from traditional network elements, like switches, routers and appliances, enabling these task-based functions to then be centralized or distributed on other (less expensive) network elements. With NFV, the various network functions are normally consolidated onto commodity servers, switches and storage systems to lower costs.

NFV and SDN are complementary technologies that can be applied independently of each other. Or NFV can provide a foundation for SDN. By using an NFV foundation combined with SDN’s separation of the control and data planes, carrier network performance can be enhanced, its management can be simplified, and new services can be more easily deployed.

VIII. DIGITAL INDIAl Digital India is an initiative by the Government of India to

ensure that Government services are made available to citizens electronically by improving online infrastructure and by increasing Internet connectivity. It was launched on 1 July 2015

l The initiative includes plans to connect rural areas with high-speed internet networks.

l Digital India has three core components.

The creation of digital infrastructurel Entertainment-real time entertainment, audio streaming,3D

gamingl Utility-remote management like securityl E-governance-Govt. sector

Delivering services digitallyDigital Literacy

Pillars of Digital India:l Broadband Highwaysl Universal Access to Mobile Connectivityl Public Internet Access Programl e-Governance – Reforming Government through

Technologyl eKranti - Electronic delivery of servicesl Information for Alll Electronics Manufacturingl IT for Jobsl Early Harvest Program.

IX. SMART CITIESSmart Cities are those that integrate information communications technology across three or more functional areas like roads, buildings, water and so on with technology to enrich the lives of its citizens. Creative platforms and killer apps have helped reduce traffic, parking congestion, pollution, energy consumption and crime. They have also generated revenue and reduced costs for residents and visitors.

Please see the link below about smart cities in Indial http://www.ndtv.com/video/player/ndtv-specials/

smart-technology-and-the-concept-of-smart-cities-in-india/374701

The Government of India has decided to make 100 cities in India as smart cities. The first phase of project Smart India with 20 cities list has been announced. It will take 3-4 years to fully develop smart city with a financial burden of about Rs.2000 crores

Smart Cities- Strategy: According to the United Nations, the global population is expected to grow from seven billion today to 9.3 billion by 2050, and the world’s cities will have to accommodate about 70 percent more residents. The traditional ways of dealing with the influx—simply adding more physical infrastructure—won’t work, given limited resources and space.


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New ways of incorporating technology will be required to provide urban services. In the future, there will be less emphasis on physical connections and more on access to virtual connections.

X. CONCLUSIONAs the internet first spread, users were amazed at the possibility of contacting people and sending information across oceans and time zones, through e-mail and instant messaging, with just a few clicks of a mouse. In order to do so, however, they typically had to sit in front of a computing device (usually a PC) and dial-up to the internet over their telephone connection. Today, with mobile internet services and the deployment of higher-speed mobile networks such as 3G (IMT-2000) and 4G (LTE), users can connect from almost any location. They can also access networks at any time, through always-on connectivity (wired and wireless broadband). The next step in this technological revolution is to connect inanimate objects and things to communication networks. This is the vision of a truly ubiquitous network–“anytime, anywhere, by anyone and anything”. In this context, consumer products might be tracked using tiny radio transmitters or tagged with embedded hyperlinks and sensors. The connectivity will take on an entirely new dimension. Today, users can connect at any time and at any location. Tomorrow’s global network will not only consist of

humans and electronic devices, but all sorts of inanimate things as well. These things will be able to communicate with other things, e.g. fridges with grocery stores, laundry machines with clothing, implanted tags with medical equipment, and vehicles with stationary and moving objects. It would seem that science fiction is slowly turning to science fact in an Internet of Things based on ubiquitous network connectivity.

Manjit Singh was President of Himachal Futuristic Communications Ltd. (HFCL), heading HFCL’s technical operations and business development. He directed the successful implementation of CDMA, GSM and WLL equipment including PDSN, billing, customer care, and SMS/VMS systems. He served on the technical groups of two world telecom forums: the International Telecommunications Union and the APT Asia Pacific Telecom. Earlier, he worked for Compton Greaves Limited as Vice President Telecom Services.

He served Government of India for over 27 years in key positions of national policy, Director responsible for maintenance and switching in the Ministry of Telecommunications and General Manager in charge of two large telecom circles in North India. He was responsible for planning, installation, commissioning, and monitoring of several large telecom networks in this period. As Chair of the India DECT Forum from 1997-1998, he played a pivotal role in promoting Wireless Local Loop technology in India and abroad. Mr. Singh is a Fellow of the IETE and holds a B.Sc. (gold medallist) degree in Electrical Engineering from the University of Punjab.

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Factors Influencing the Adoption of Internet Banking in Selected Banks of Ethiopia — a Study

Dr. Girish Kumar PainoliDepartment of Business Studies, Shinas College of Technology, Shinas, Sultanate of Oman

[email protected]

Abstract — The breakthrough in information technology occasioned by the introduction of the telecommunications networks and the computer system persist to shape the way banks and their corporate relationships are structured worldwide. The pressure of globalization, consolidation, deregulation and rapidly changing technology made it necessary for banks to re-examine their service delivery systems to suitably position them within this dynamism of information technology.

This research paper is an attempt to examine the factors that play vital role in adoption of internet banking in different banks of Ethiopia. In this research commonly applied empirically supported models of information technology are used in addition to variable Perceived security. This research paper is an attempt to find all the factors which are causes in adoption of internet banking in selected banks of Ethiopia, more specifically in the research area.

Keywords: Internet banking, Technology acceptance model, Commercial banks.

I. INTRODUCTIONSERVICE industry in the world is changing via new technology leading to the way customers are served in many service organizations. Geographical distance has lost its meaning and service availability, convenience, and speed of service distribution determine competitive advantage for organizations, such as banks. To compete in the complex environment, they are forced to deliver the newest and most attractive services that customers are demanding. Many banks in the world offer electronic services which release them from limitations of time and place, providing round the clock services to customers.

Ethiopia has not yet enacted legislation that deals with E-commerce concerns including enforceability of the validity of electronic contracts, digital signatures and intellectual copyright restricting the use of encryption technologies. Low literacy rate is a serious impediment for the adoption of E-banking in Ethiopia as it hinders the accessibility of banking services. For citizens to fully enjoy the benefits of E-banking, they should not only know how to read and write but also possess basic ICT literacy.

E-banking, is a system that enables banks to offer their customers access to their accounts to transact business and obtain information via electronic communication channels such as Automated Teller Machines (ATMs), telephone-banking, home banking , TV based banking (private dialup) and internet banking is becoming a common practice across the developed world [1]. This study focuses on one component of E-banking that is Internet banking. Internet banking is different from Electronic Banking (e-banking) in that the latter is a higher level activity that encompasses not only internet banking, but also Telephone Banking, ATM, TV-banking and other electronic payment systems that are not operated through the Internet.

Currently in Ethiopia Internet banking service is adopted in three commercial banks in Ethiopia, namely; Zemen Bank, United Bank and Commercial Bank of Ethiopia, though the internet banking service in the country is still at infant stage.

The major internet banking activities provided by those banks are: sending money to individuals or companies, keeping track of their account, knowing loan status, transferring money from one of your numerous accounts to another of your account and transferring money from your account to another bank customer account.

Objectives Of The Study: The present study is based up on the following objectives in relation to the factors which influence directly or indirectly in adoption of internet banking by the selected banks of Ethiopia.

l To identify the impact of usefulness and ease to use on attitudes of individuals towards the use of internet banking service.

l To investigate the direct and indirect effect of ease of use towards the adoption of internet banking.

l To investigate the impact of security and usefulness on the behavioral intention towards the usage of internet banking in selected commercial banks of Ethiopia.

l To examine the effect of behavioral intention to use on actual usage of internet banking service.

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Significance of the Study: The finding of this study helps banking institutions to be familiar with those factors that both adversely or favorably affect the adoption of Internet banking solution and take corrective measure to expand internet banking service.

In addition, the study is useful for policy makers to make well-versed decisions by indicating what has to be considered while different rules are set regarding to adoptions of internet banking solution, and also the experience in making the study will enhance and enrich the knowledge of the researcher.

This study will also encourage academician and other interested researchers to carry out more extensive studies in this area.

Scope of the Study : The scope of the study is limited to users of internet banking in Adama and Addis Ababa. Addis Ababa is one of the largest and commercial center in Ethiopia which ensures a wide spread of potential respondents to the study and the Adama is a city where enormous business activities are carried out by using available modern banking services

Limitation of the Study: The sample in the present study is limited to customers of Addis Ababa and Adama; different results are possible from customers in other Ethiopian cities.

The strategy of data collection also represents a limitation. The use of customer intercept surveys might lead to omission of some customers who do not visit physical bank branches within the time frame of the study.

Hypothesis of the Study: The present study is based on the following hypothesis, which will be base to the study and findings of the study they are:

H1: Perceived ease of use positively influences the perceived usefulness of the use of internet

H2: Perceived ease of use positively influences the attitude towards the use of internet banking

H3: Perceived usefulness positively influences the intention to use internet banking

H4: Perceived usefulness positively influences the attitude towards the use of internet banking.

H5: Attitude positively influences the intention to use internet- banking

H6: Perceived behavioral intention will have a positive effect on the frequency of Internet banking use.

H7: Perceived Security has positive relationship with customer’s Intention to use.

III. RESEARCH METHODOLOGYSource of Data and Collection Methods: This study has been conducted by using primary sources of data through structured

questioners from internet banking servicer users of selected commercial banks in Addis Ababa and Adama. And also secondary data wherever necessary for the study.

Sampling Design and Sample Size : Three commercial banks that adopted internet banking solution were selected for the study i.e. one state owned bank Commercial bank of Ethiopia and two private banks Zemen bank and united bank .

According to survey total internet banking users of selected banks of as on December, 2013, are 14,253.

Commercial Bank of Ethiopia- 1,035,Zemen bank - 3,218United bank -9,990.

Following formula will be used to calculate the sample size.

At 95% confidence level and P =0.5 are assumed for Equation.N = N/[1 + N(e)2]

where n is the sample size, N is the population size, and e is the level of precision.

Therefore, by considering the above formula, the researcher selects a sample of 400 respondents from the total population to make sound conclusion about the population.

Those respondents have been selected proportionately from each selected commercial banks and simple random sampling technique has been employed in order to select respondents of each selected bank.

Commercial banks which started internet banking solution and customers registered for internet banking service after December 2013 were not considered.

IV. DATA ANALYSIS AND INTEREPRETATION Descriptive Statistic analysis

TABLE 1 -- BANK WHICH USES IB SERVICES

Banks Frequency %

Zemen Bank S.Co. 88 22.6

United Bank S.Co 273 70.2

Commercial bank of Ethiopia 28 7.2Total 389 100.0

Source: Field Survey

It can be observed from Table 1 and Figure 1 that, proportion of internet banking service customers of commercial banks. 26.0%

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of the respondents are of Zemen Bank, 70.2% of United Bank and 7.2% of the Commercial Bank of Ethiopia. Therefore, a great number of internet banking users belong to United Bank. This indicates that state owned bank is still behind private banks in terms of internet banking.

TABLE 2 -- INTERNET BANKING SERVICE USAGE BASED ON PERIOD OF USAGE

IB service usage years Frequency Percent

Less than one year 113 29.01year - >3 year 218 56.03 years – 6 years 57 14.7longer than 6 years 1 .3Total 389 100.0

Source: Field Survey)

TABLE 3 -- SUMMARY OF DESCRIPTIVE STATISTICS

Variables Frequency % Mean Max. Min. SD

Actual usage 1.81 4 1 .933

Up to 10 times 177 45.5

11 to 20 times 145 37.3

21-30 times 31 8.0

Over 30times 36 9.3

Total 389 100.0

Perceived Ease of Use 4.55 5 3 .626

Neutral 28 7.2

Agree 119 30.6

Strongly agree 242 62.2

Total 389 100.0

Perceived usefulness 4.80 5 4 .397

Agree 76 19.5


Total 389 100.0

Attitude 4.49 5 1 .918

Strongly disagree 11 2.8

Disagree 16 4.1

Neutral 1 .3

Agree 103 26.5


Total 389 100.0

Intention to use 4.49 5 1 .918

Strongly disagree 9 2.3

Disagree 9 2.3

Neutral 9 2.3

Agree 137 35.2

Strongly agree 225 57.8Total 389 100.0Perceived Security 4.38 5 1 .749

Strongly disagree 1 .3

Disagree 3 .8

Neutral 48 12.3Agree 132 33.9


Total 389 100.0(Source: Field Survey)

Descriptive statistic for dependent variables: Actual use of Internet banking was measured with a 5-point Likert scale to record agreement with overall frequency of use in prior 30

Figure 1. Bank using IB services. Source: Field Survey

Figure 2. Internet Banking Service based on period of usage.Source: Field Survey

It can be observed from Table 2 and Figure 2 that, there is a big variation in terms of usage of internet banking based on usage period. More percentage is found in 1-3 years of usage i.e. 56% this fact indicates that the customers are slowly moving towards internet banking as banks moving to adopt the internet banking system. This fact may be due to various reasons among all country’s economy and infrastructure situations.

INTERNET BANKING

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days, an absolute estimate of use in the same period and the mean value of actual usage of internet banking service is 1.81.

This indicates that the 45.5% respondents responded that they used less than 10 times within last 30days where 37.76% respondents responded that they used up to 11-20 times with in last 30days.

Descriptive statistic for in dependant variables: The study also attempted to know how much usage of internet banking is easy for the customers or for respondents and the mean value for perceived ease of use is 4.55. This indicates that 30.6% respondents replied that they agree with ease of using of internet banking and 62.2 % of respondents replied that they strongly agree with ease usage of internet backing. From descriptive statics table, it can be seen that most of the respondents strongly agreed that internet baking is easily usable, learnable, flexible to interact with it, and it does not need complicated knowledge. From 389 respondents only 28(7.2%) of them did not give any responses on questions related with perceived ease of use of internet banking.

Further, it was attempted to assess the usefulness of internet banking in the life of respondents. From Table 3, it can be observed that the mean value for perceived usefulness is 4.8, indicating that 80.46% strongly agree with usefulness of internet banking. Besides, 19.5% agreed with the usefulness of internet backing. Most of the respondents strongly agreed with usefulness of internet baking and they replied that internet baking is time saver and improves the performance of utilizing banking services.

In addition, the study attempted to assess the attitude of respondents towards internet banking and the mean value of attitude is 4.9. This indicate that 66.32 % of respondent strongly agreed that using of internet banking creates attitudinal change: they responded, internet banking transaction is a good idea, pleasant, and the wise idea.

Meanwhile, the study attempted to assess what is intention of the respondents to use internet banking. Table 3 shows that the mean value of intention to use internet banking is 4.44, indicating that out of 389 respondents, 225 (57.8%) and 137 (35.2%) strongly agree and agree respectively with future using of Internet Banking, regular base using of Internet Banking and they recommended others so as to use internet banking .

Finally, the study investigated that security of internet banking and the mean value of perceived security is 4.38, revealing that 205 (52.7%) and 132 (33.9%) of them strongly agree and agree with security of internet banking.

Therefore, it can be observed that, the most of the respondents strongly agree with the security of internet banking. This means

that using of internet banking is highly secured; it uses to transmit sensitive information and provides mental satisfaction during transmitting personal or sensitive information.

Econometric Analysis: (Diagnostic test) to show how the estimation technique used for this study is appropriate and the hypothesis tests regarding the coefficient estimates are correctly made, a diagnostic test was conducted by using SPSS software.

Goodness of fit of tests:Goodness fit test through R2

To examine the factors influencing the adoption of internet banking, the researcher included five explanatory variables (perceived ease of use, perceived usefulness, attitude, intention to use and perceived security) and one dependent variable (Actual usage).

The goodness of fit of the model can be measured by the square of the correlation coefficient also called R2. The most common goodness of fit statistic is R2. That R2 is the square of the correlation between the value of the dependent variable and fitted values from the model. This square of the correlation coefficient (R2) is always lying between 0 and 1. If this correlation is high (close to one), the model fits the data well, while if the correlation is low (close to zero), and the model is not providing a good fit to the data.

Consequently, as it is shown on table 4.4 the value of adjusted R2 is 0.559, indicating that the independent variables in the model are explaining 56% of the variations on the dependent variables. It can be seen that the model of the study is providing a good fit to the data.

Goodness fitness through ANOVA.

The significance value of F-statistic or regression model in general, from the table shows 0.000. Thus, the statistical significance of the regression model that is used for the study is less than 0.05. (i.e. P < 0.000). It is indicating that, over all, the model used for the study is significantly good enough in explaining the variation on the dependent variable.

Test of Multi Collinearity: Multi Collinearity is defined as the extent to which a variable can be explained by other variables in the analysis or an explanatory variable demonstrates near linear dependence with another explanatory variable.

The effects of multi-collinearity make it difficult to determine the contribution of each independent variable as the effects of independent variables are mixed or confounding. Problems of multi-collinearity among predictors can result in an overestimation of the standard deviation of the regression coefficients. Tolerance above 0 1, Variance Inflation Factor (VIF) value below 10 indicates no major multi-collinearity

55

TABLE 4 -- GOODNESS FIT TEST THROUGH R2

Model SummaryModel R R Square Adjusted R

SquareStd. Error of the

EstimateChange Statistics Durbin-Watson

R Square Change F Change Sig. F Change1 .751a .564 .559 .249 ..559 .907 .000 1.965

a. Predictors: (Constant), Perceived Security, Attitude, Perceived Ease of Use, Perceived usefulness, Intention to useb. Dependent Variable: Actual usage(Source: Field survey and SPSS)

TABLE 5 -- GOODNESS FITNESS THROUGH ANOVA

Model Sum of Squares Df Mean Square F Sig.

1Regression 3.956 5 .791 .907 .000b

Residual 333.967 386 .872Total 337.923 389

a. Dependent Variable: Actual usageb. Predictors: (Constant), Perceived Security, Attitude, Perceived Ease of Use, Perceived usefulness, Intention to use

TABLE 6 -- SUMMARY OF REGRESSION ANALYSIS

Hypothesis Dependent variable Independent variable β t-value p-value Collinearity Statistics

Tolerance VIF

H1 Attitude Perceived ease of use 0.379 5.725 0.000 1.000 1.000

H2 Perceive usefulness Perceived ease of use 0.675 10.611 0.000 1.000 1.000

H3 Intention to use Perceive usefulness 0.408 6.764 0.000 1.000 1.000

H4 Attitude Perceive usefulness 0.392 6.359 0.000 1.000 1.000

H5 Intention to use Attitude 0.788 25.138 0.000 1.000 1.000

H6 Actual usage Intention to use 0.387 0.227 0.060 1.000 1.000

H7 Intention to use Perceived security -0.011 -1.218 0.081 1.000 1.000

issues. It can be observed that, the Tolerance and VIF values at both cases are 1.00 of individual output. It can be concluded that there is no problem of multi-collinearity in this study.

In addition to this the presence of multicollinearity can also be tested using the correlation matrix. The result of the correlation matrix if, not greater than the maximum index of 0.80 Thong (1999). Hence in the study the correlation of the variables has a maximum figure of 0.787, qualifying no multi Collinearity.

Test of autocorrelation: The test for autocorrelation was made by using Durbin and Watson (1951). Durbin--Watson (DW) is a test for first order autocorrelation i.e. it tests only for a relationship between an error and its immediately previous value. DW is approximately equals to 2(1 − ˆρ), where ˆρ is the estimated correlation coefficient between the error term and its first order lag (Brooks 2008). There for at this study the calculated DW is 1.965 and this is nearer to 2, definitely has no auto correlation problem.

Test of normality: Normality test was performed by using a histogram and plotting the normal probability plot (p-p plot). If the histogram appears to at least resemble a bell shape curve and all the residuals were located along the diagonal line of p-p plot, it was assumed that the normality requirement has been met.

Figure 3: HistogramSource: Out of SPSS, 2014

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TABLE 7 -- PEARSON’S CORRELATION COEFFICIENTS OF THE STUDY VARIABLES

Correlations

Variables Actual usage

Perceived Ease of Use

Perceived usefulness

Attitude Intention to use Perceived Security

Actual usage Pearson Correlation 1 .296* .125** .025 .112 -.090

Sig. (1-tailed) .030 .001 .209 .061 .006

N 389 389 389 389 389

Perceived Ease of Use Pearson Correlation 1 .475** .281** .200** .047

Sig. (1-tailed) .000 .000 .000 .177

N 389 389 389 389

Perceived usefulness Pearson Correlation 1 .307** .188** .069

Sig. (1-tailed) .000 .000 .088

N 388 389 389

Attitude Pearson Correlation 1 .787** .010

Sig. (1-tailed) .000 .423

N 389 389

Intention to use Pearson Correlation 1 .049

Sig. (1-tailed) .169

N 389

Perceived Security Pearson Correlation 1

Sig. (1-tailed)

N 389* Correlation is significant at the 0.05 level (1-tailed).** Correlation is significant at the 0.01 level (1-tailed).

Source: SPSS output

Figure 4. Normal p.p plotSource: Field survey and SPSS

Therefore, in this study the data are normally distributed. It can be concluded that, no problem of normality. In fact the dotted on the plot line seems near away from the line passing through the origin, but this is due to large number of observation.

Reliability of Measurement: Cronbach’s alpha test showed an acceptable degree of internal consistency in the scales and groups we considered, being in all the cases over the 0.7. As indicated in the table, the test result is between 0.702 and 0.894 i.e. Cronbach’s alpha of Perceived ease of use (PEU) is 0.793, 0.888 for Perceived usefulness (PU), 0.723 for Attitude (ATT), 0.894 for Intention to use (ITU), and Cronbach‘s alpha of Perceived Security is 0.702. Therefore, based on the test, the results for the items are reliable and acceptable.

4.2.3 Model Specification: To test the hypotheses formulated a series of simple linear regression analyses was conducted to calculate direct and indirect path coefficients. Simple linear regression is a useful statistical method for exploring the relationship between dependent and independent variables and can be described by the following equation: Y= a +bx

57

where “x” and “y” are classed as independent and dependent variables and “b” is the slope of the line and “a” is the intercept i.e. where the line cuts the y-axis.

The full regression model for determinants of actual usage of internet banking is, given as follows:

IBAU = α +β1PEOU+ β2 PU+ β3 ATT+ β4ITU+ β5PS + ε

where:AU Actual usage of internet banking,PEOU perceived ease of use, PU perceived usefulness,ATT Attitude of customers,ITU Intention to use,PS perceived Security and ε is the error term for any missing variable, assumed

to distribute normally with zero mean and σ standard deviation and is independent of the error terms associated with all other Observations.

α the intercept value of the regression surface.

Hypotheses testing and interpretation of results: Hypotheses are considered supported when path coefficients are significant at the 0.05 level. The path coefficients were calculated using simple linear regression technique for the following:

Perceived ease of use and Attitude: Hypothesis H2, that Perceived ease of use positively influences the attitude towards the use of internet banking, was supported (β = 0.379, t = 5.725 and p < .001). This result is consistent with the findings of prior studies that used either TAM model (Wang et al. 2003). This suggests that if bank customers perceive an Internet banking system is easy to use, they might adopt that system or use it in preference to other Internet banking systems perceived as hard to use and statistically significant at 1%.

Perceived ease of use and perceived usefulness:Hypothesis H1, that Perceived ease of use positively influences the perceived usefulness of the use of internet banking was supported (β = 0.675, t = 10.611 and p < .001). It is consistent with findings of prior studies. The path coefficient values for perceived

ease of use to perceived usefulness was higher than values for perceived ease of use to attitudes towards the use of internet banking, which indicates that although the direct effects of perceived ease of use on to users attitude remain important over the time but indirect through perceived usefulness will be more weighted by the existing users as their experience with Internet banking system increases.

Both the hypotheses H1 and H2 thus support argument that “perceived ease of use may actually be an informal predecessor to perceived usefulness, as opposed to a parallel, direct determinant of system usage and 1% significant level.

Perceived Usefulness and Intention: Hypothesis H3, that Perceived usefulness positively influences behavioral intention to use internet banking, was supported (β = 0.408, t = 6.764 and p < .001). The result is expected and consistent with prior studies that used TAM in Internet or mobile banking context. This suggests that if banks customers perceive Internet banking to be a useful to carry out financial transactions than traditional branch banking, they will adopt or use the services, and at 1% statistically significant.

Perceived usefulness and attitude for internet banking services: The hypothesis H4, that Perceived usefulness positively influences the attitude towards the use of internet-banking, was supported (β = 0.392, t = 6.285 and p < .001), which was expected since most of the studies that uses and have found perceived usefulness is one of the key factor that influence attitude adoption or use of Internet banking services Chau (2000) and Pikkarainen et al. (2004) This suggests that if bank customers perceive that Internet banking has a useful over branch banking in accessing accounts from any location and at any time, and provides greater control and flexibility in managing their accounts, they may adopt it and use it, and 1% significant level.

Attitude and intention to use internet banking services: The support (β = 0.788, t = 25.138 and P < .001) for hypothesis H5 that Attitude positively influences the intention to use internet banking the findings of the result showed that Internet banking services in Ethiopia fitted with the hypothesis and the technological acceptance model.

Intention to use and Actual usage of internet banking services: Actual usage was measured as the number of times in a month user used Internet banking services. The hypothesis H6 that, Perceived behavioral intention will have a positive effect on the frequency of Internet banking usage is not supported (β = 0.387, t = 0.227 and p >.001) and the result conflicts with findings of prior study.

Perceived security and intention to use internet banking service: There was a weak and negative relationship between perceived

TABLE 9 -- SUMMARY OF RELIABILITY TEST RESULT

Category (Item) Number of Item in the category

Cronbach’s Alpha

Perceived ease of use (PEU) 5 0.793

Perceived usefulness (PU) 6 0.888

Attitude (ATT) 4 0.723

Intention to use (ITU) 4 0.894

Perceived Security 4 0.702

Source: SPSS

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security and intention to use Internet banking. Consequently, hypothesis H7, that Perceived Security has positive relationship with customer’s Intention to use internet banking, was not supported (β = -0.011, t = -1.218 and p .>.001). This conflicts with the findings of prior studies Chan and Lu (2004) and Pavlou (2001). Perceived security associated with Internet banking have been found major obstacle to Internet banking adoptions in many countries across the world. One explanation for the deviation from could be that respondents did not perceive security associated with Internet banking system, and in significant at 5% and 1% significant level.

V. FINDINGSFindings of the Study: Based upon the above discussion and findings following recommendations are given:

l The result of the study was found to influence perceived ease of use either directly or indirectly through its effects on attitude or perceived usefulness.

l The perceived ease of use was found to affect directly attitudes towards adoption of internet banking significantly, which confirms the importance of the role of ease of use variable that reflects users’ concern of effortlessness of the Internet banking environment and confirms that difficulty of use can discourage attitude. Therefore, banks adopt as easy as possible adopting in internet banking services.

l Perceived ease of use exhibited a significant indirect effect on attitudes towards adoption of internet banking through perceived usefulness. This suggests that the easier Internet banking is to use, the greater will be a user’s feeling of determination and which in turn might motivate user to explore features and benefits of service and thereby increase perceived system usefulness. Therefore banks, should adopt internet banking that is easy to use and more useful.

l The results of regression analysis indicated that perceived usefulness was found to be the most significantly related factor affecting intention. This confirms the importance of perceived usefulness in explaining adoption or use of a new technology.

l If Internet banking is to be accepted by the users, they should perceive it to be useful, quicker and easier way of carrying

out internet banking service than traditional branch banking system.

l It was found that difficulty of use can discourage intention to adopt or use of a useful system but no amount of ease of use can compensate for a system that is not found useful by users. Therefore commercial banks of Ethiopia must not over stress ease of use at the expense of overlooking the usefulness of Internet banking.

l The study exhibited that, failed to support for impact of intention to use suggests that respondents viewed it as an insignificant factor that could motivate their actual usage of Internet banking. Therefore the issue of usage construct treated as less critical by respondents.

l The security issues viewed it as an insignificant. In Ethiopia could be that, respondents did not perceive security issues associated with Internet banking services since security violation crises have not been publicly reported till now.

l Another possible factor could be that the measures of security used for this research might not suitable for the Internet banking context, although they were adopted from prior studies conducted in other countries.

l Therefore, commercial banks in Ethiopia should not much consider security issues problem in users’ side in adopting internet banking, unlike other countries. In fact this opportunity will reduce setup cost of adoption of internet banking.

l In adoption of internet banking customer should be mostly taken into consideration for its better adoption and implementation.

l Better the services provided better expansion of whole banking system can be expected.

l State owned banks need to do more in this regard because study reveals that the users of internet banking are more with private commercial banks rather than state owned one.

VI. CONCLUSIONBanking is one of the significant factors of entire economy of the any country. Stronger the banking system stronger and stable is the economic system. Since most of the African region suffers from lack of infrastructure especially in electronic media

TABLE 10 -- SUMMARY REGRESSION ANALYSIS

Hypothesis Dependent variable Independent variable Β t-value p-valueH1 Perceive usefulness Perceived ease of use 0.675 10.611 0.000

H2 Attitude Perceived ease of use 0.379 5.725 0.000

H3 Intention to use Perceive usefulness 0.408 6.764 0.000

H4 Attitude Perceive usefulness 0.392 6.359 0.000

H5 Intention to use Attitude 0.788 25.138 0.000

H6 Actual usage Intention to use 0.387 0.227 0.060

H7 Intention to use Perceived security -0.011 -1.218 0.081

59

therefore there is an urgent need to develop and practice the internet banking on a war basis.

Similarly when the banking system is strong and equipped with all the modern techniques and infrastructure, it boosts the financial transactions from all over the world. And when money gets transfer from all the corners automatically economy will get boost because the nation will get connected to world’s most financial sectors.

Internet banking will definitely encourage its existing customer and potential customers to adopt the same. This will encourage them to carry more banking transaction through internet.

Developed countries of the world are enjoying the benefits of innovation in information technology and they are implementing it to all the service sectors including banking which is one of the significant factors of the economy.

The present study revealed the various factors that influence the adoption of internet banking in Ethiopia. So precisely the concerned authority should take immediate steps to avoid difficulties in adoption of internet banking in this area so that the benefits of internet banking can be enjoyed and economy can be developed.

The banking sector of Ethiopia has to cover internet banking services by introducing the new software and technologies like electronic banking, mobile banking, international banking services and more ATM machines in all of its banks.

VIII. REFERENCES[1]. Pikkarainen, T., Pijjarainen,K, Karjaluoto,H and Pahnila,S.

Consumer acceptance of online banking: an extension of the technology acceptance model. Internet Research, Volume 14, No. 3, pp.224-235, 2004.

[2]. Agarwal, R., & Prasad, J. The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies. Decision Science, Volume 28, No.3, pp.557-582, 1997.

[3]. Biritu, Financial Sector Development in Ethiopia; Trends and risks, NBE, August, 2011

[4]. Chen, L.-D. and Tan, J., ‘Technology Adaptation in E-Commerce: Key Determinants of Virtual Stores Acceptance’, European Management Journal, Volume 22, No. 1, pp. 74-86, 2004.

[5]. Daniel, E. Provision of electronic banking in the UK and the Republic of Ireland. International Journal of Bank Marketing, Volume 17, No. 2, pp. 72-82, 1999.

[6]. Davis, F.D. and Venkatesh, V., ‘A Critical Assessment of Potential Measurement Biases in The Technology Acceptance Model: Three Experiments’, International Journal Human-Computer Studies, Volume 45, No. 1, pp. 19-24, 1996.

[7]. Henderson, R. and Divett, M.J. , ‘Perceived Usefulness, Ease of Use, and Electronic Supermarket Use’, International Journal Human-Computer Studies, Volume 59, No. 3, pp. 383-395, 2003.

[8]. Kolodinsky, J.M., Hogarth, J.M. and Hilgert, M.A. The Adoption of Electronic Banking Technologies by US Consumers; International Journal of Bank Marketing, Volume 22, No. 4, pp. 233 – 241, 2004.

[9]. Mathieson, K., Peacock, E. and Chin, W. W., ‘Extending the Technology Acceptance Model: The influence of perceived user resources’. Database for Advances in Information Systems, Volume 32, No.3, pp. 86-112, 2001.

[10]. Mols, K., “The Behavior Consequences of PC Banking”, International Journal of Bank Marketing, Volume 16, No.5, pp.195-201, 1998.

[11]. M. Tan and T. S. H. Teo, “Factors influencing the adoption of Internet banking,” Journal of the Association for Information Systems, Volume 1, No. 5, pp. 1–44, 2000.

[12]. Nysveen, H, Pedersen, P. and Thorbjornesn , H. Intentions to Use Internet Banking Services: Antecedents and Cross-Service Comparisons. Academy of Social Science Journal; Summer 2005; p. 33, 2005.

[13]. Nor, M. and Pearson, J. The Influence of Trust on Internet Banking Acceptance. Journal of Internet Banking and Commerce, Volume 12, No.2, pp. 1-10, 2008.

[14]. Roberts, P. and Henderson, R., ‘Information Technology Acceptance in A Sample of Government Employees: A Test of the Technology Acceptance Model’, Interacting with Computers, Volume 12, No. 5, pp. 427-443, 2000.

[15]. Sathye, M. ‘Adoption of Internet banking by Australian consumers: an empirical investigation’, International Journal of Bank Marketing, Volume 17, No. 7, pp. 324-334, 1999.

[16]. Tan, M. and Teo, T. S. H. Factors Influencing the Adoption of Internet Banking. Journal of the Association for Information Systems, Volume 1, No.5, pp. 1-42, 2000.

[17]. Thulani, D, Tofara, C. and Langton, R .“Adoption and Use of Internet Banking in Zimbabwe: An Exploratory Study,” Journal of Internet Banking and Commerce, Volume 14, no. 1, 2009.

[18]. Venkatesh, V. and Davis, F. D., ‘A Model of the Perceived Ease of Use: Development and Test’. Decision Science, Volume 27, No. 3, pp.451-481, 1996.

[19]. Venkatesh, V. and Davis, F.D., ‘A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies’, Management Science, Volume 46, No. 2, pp. 186-204, 2000.

Dr. Girish Kumar Painoli received the M.Com degree, from Osmania University, Hyderabad, in 1995, M.Phil degree from SGB Amaravathi University in 1999 and Ph.D. degree in management Science, from Swami Ramanand Teerth Marathwada University Nanded in 2012. He also qualified UGC-NET. He worked as Professor in Department of Accounting and Finance at Adama Science and Techonology University, Adama, Ethiopia.Currently, he is a Faculty in Accounting in Department of Business Studies at Shinas College

of Technology, Al AQR, Shinas, Sultanat of Oman. His teaching and research areas include Accounting and Finance. Authored/co-authored approximately twenty five research papers and attended over 25 seminars.

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Vibrational Study of Aspartic AcidsDr. Santosh Kumar

Department of Applied Sciences, IEC Group of Institutions, 4, Knowledge Park-I, Greater Noida 201306 UP [email protected]

Abstract — As partic acid is a type of amino acid which is essential for growth of body. Author studied the IR and Raman Spectroscopy of the molecule in the range of 4000-400 cm-1 and recorded the UV visible spectra of As partic acid in the range 400-200 nm at different concentrations and pH values. Several peaks were assigned.

Keywords: Vibrational study, Aspartic acid, Raman spectrum.

I. INTRODUCTIONMOST of the amino acids exist in biological systems in the L-form [1-3]. Aspartic acid recemises from the L- to the D- form in living as well as non living systems at a rate of about 0.12-0.14٪ per year [4-10]. This fact can be used to determine age and due to which aspartic acid has a place of special interest amongst the amino acids [4-10].

Aspartic acid is a non–essential amino acid and found in abundance in plant proteins. Both aspartic acid and glutamic acid and almost all proteins are linked to other amino acids only through their side carbonyl groups. Some of the amino acids that are synthesized from aspartic acid are arginine, asparagines, lysine, methionine, threonine, isoleucine and different nucleotides. It is important from this point of view also Aspartic acid is needed for stamina, brain and neutral health and assists the liver by removing excess ammonia and other toxins from the blood stream. Its role is important in function of RNA, DNA, as the production of immunoglobulin and anti body synthesis. [11]. Aspartic acid forms a dianion at high pH and a monocation at low pH, thus existing in species of different stoichiometry. There are two tautomeric zwitterionic structures for Aspartic acid, and each may have different rotamers.

Nagy and Noszal [12] reported theoretical calculations with available experimental results for the conformational/tautomeric equilibrium of aspartic acid zwitterionic aqueous solution. Navarrete et al. [13] studied the Infrared and Raman spectra of aspartic acid dipeptide and glutamic acid dipeptide solid samples. Wang and Ando [14] have reported a study of structure and dynamics of poly aspartic acids sodium blends by CCP/MAS NMR method. Mary and Ramkrishnan[11] made IR and Laser Raman spectral studies of D, L– aspartic

acid [15-17]. In this paper the infrared, Raman spectra of aspartic acid in the 400-4000 cm-1 region were studied. Also, the electronic spectra of this molecule at different concentrations as well as at different pH values were studied.

II. RESULTS AND DISCUSSION The infrared and Raman spectra of aspartic acid are shown in Figures 1 and Figure 2 respectively. A band is observed in the infrared spectrum at 3134 cm-1 due to symmetric stretching of NH3

+, but corresponding band is absent in Raman spectrum. In this region of spectrum Navarrete et al. [13] reported an intense peak at 3115 cm-1 in IR spectrum. A peak is observed at 3042 cm-1 in IR spectrum. This is assigned to CH2 stretching (asym). This peak does not appear in Raman spectrum. Navorrete et al. [13] also observed this peak at 3021 cm-1 and similar assignment has been made by these workers. Similarly a band has been observed at 2924 cm-1 due to asymmetric stretching of CH2 group in I.R. spectrum but not seen in the Raman spectrum. There are two bands at 2879, 2843 cm-1 in Raman spectrum due to symmetric stretch of CH2 group but these bands are not seen in IR spectrum.

There is a band at 1685 cm-1 due to asymmetric stretching of COO- observed in both IR and Raman spectrum. Similarly a band appears at 1618 cm-1 in IR and at 1620 cm-1 in Raman spectrum due to asymmetric stretch of COO-.In IR spectrum there is a band at 1504 cm-1 and its corresponding band is seen in Raman spectrum at 1540 cm-1.These peaks are considered due to symmetric bending of NH3

+. There are three bands in Raman spectrum within the region of 1400-1487 cm-1 at 1487, 1418, 1400 cm-1 .These peaks are assigned as bending of CH2 group, symmetric stretch of COO- group and combined effect of stretching of C=O + OH Bending respectively. Due to bending of CH group, there are two bands observed at 1333 cm-1 and at 1361cm-1 in Raman spectrum but only a single band appears in IR spectrum at 1346 cm-1.

This is considered to be due to the combined effect of bending of OH group and stretching of CC bond. There is a peak at 1311 cm-1 in IR spectrum and at 1287 cm-1 in Raman spectrum. There are two bands due to torsional motion of CH2 group at 1251cm-1 and at 1210 cm-1 in Raman spectrum but only one band is seen

61

at 1213 cm-1 in IR spectrum. The rocking of NH3+ group leads

to two bands in Raman spectrum at 1113 cm-1 and 1139 cm-1. Due to stretching of CN group as well as stretching of CC bond, there are bands observed in IR spectrum at 1070 cm-1 and in Raman spectrum at 1072 cm-1. A band is observed at 1033 cm-1 in IR spectrum and is assigned as due to stretch of CN group. Its corresponding band does not appear in Raman spectrum.

A band is seen at 980 cm-1 in Raman spectrum due to stretching of CN as well as CC bond but not observed in IR spectrum. Similarly an intense band is observed at 934 cm-1 in Raman spectrum due to out of plane bending of OH group which are not seen in IR spectrum. Due to rocking of CH2 group there is a band at 893 cm-1 in IR spectrum. A band is seen in Raman spectrum also at the same frequency .A similar band is seen at 852 and 857cm-1 respectively again due to rocking of CH2

group. There are two bands in Raman spectrum at 733 cm-1 and 778 cm-1 due to bending of COO- group but corresponding bands do not appear in IR spectrum.

A band at 695 cm-1 due to COOH group observed in Raman spectrum which does not appear in IR spectrum. There is a band at 640 cm-1 in IR and at 643 cm-1 in Raman spectrum. This is due to bending of COO- group. There also appears a band in Raman spectrum at 586 cm-1 due to bending of COO- group but not seen in infrared spectrum of this molecule. A band is seen at 500 cm-1 in IR and at 510 cm-1 in Raman due to bending of HOCC bond. Due to bending of NCC as well as of bending of OCC a band appears in IR at 476 cm-1 and in Raman at 487 cm-1 respectively. The deformation motion of NH2 group leads a band at 418 cm-1 in IR spectrum but not seen in Raman spectrum. These bands are tabulated in Table 1.

TABLE 1-- A COMPARISON OF IR AND RAMAN FREQUENCIES OF ASPARTIC ACID

S. NO. IR Frequencies(cm-1)

Raman Frequencies(cm-1)

Assignment

1.2.3.4. 5.6.7.8.9. 10. 1112.13.14. 15.16. 17. 18.19. 20. 2122. 23. 24. 25. 26.27. 28. 29. 30. 31. 32.

323430422132--------

168516181504----------------

13461311----

1213--------

10701033--------893852------------640----500476418

------------

2879284316851620154014871418140013611333128712511210113911131072----980934893857778733695643586530487----

Symmetric stretchNH3+

Asy Stretch of CH2Asy Stretch of CH2Symmetric stretchCH2Symmetric stretchCH2Asymmetric Stretch of COO-

Asymmetric Stretch of COO-

Symmetric Bending NH+3

Bending CH2Symmetric Stretch COO-

Stretch CO,Bending OHBending CHBending CHBendingOH, Stretch COTorsion CH2Torsion CH2Rocking NH3

+

Rocking NH3+

Stretch CN, Stretch CCStretch CNStretch CN, Stretch CCOut plane Bending OHRocking CH2Rocking CH2Out plane Bending COO-

Bending COO-

Bending COOHBending COO-

Bending COO-

Out plane Bending HOCCBending NCC,Bending OCCDeformation NH2

Electronic absorption spectrum:

VIBRATIONAL STUDY OF ASPARTIC ACIDS

62


Electronic absorption spectrum: The electronic absorption spectrum of the same molecule was recorded (Figure 3) by taking 0.01 gm in 4 ml distilled water in region 200-400 nm at pH = 7. In this case peaks appear at 206 nm. On changing the pH of this solution peaks are seen at 204 nm and at 224 nm at pH = 2 and pH = 10 respectively.

Figure 1. Infrared spectrum of aspartic acid in solid form.

Figure 2a. Raman spectrum of aspartic acid

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Figure 2b. Infrared spectrum of aspartic acid in solid form.Raman Shift(cm-1)

Figure 3. Electronic absorptiom spectrum of aspartic acid at different pH values.

III. CONCLUSIONThe observed IR and Raman peaks are in good agreement mutually. The observed peaks have also been supported by others. Some unobserved peaks have also been monitored.

IV. REFERENCES[1] A. L. Lehninger, Principles of Biochemistry, CBS Publishers

& Distributors, Delhi, pp. 97-98, 1987. [2] L. Geoffreg and Zubay, Biochemistry, Eds Wesley Publishing

Company, Inc. USA, p 7, 1984.

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[3] R. W. Mcgilvery and G. Goldstein, Biochemistry: A Functional Approach, W. B. Saunders Company USA p 15, 1979.

[4] P. M. Helfman and J. L. Bada, Proc. Nat. Acad. Sci. USA, Volume 72, p.2891, 1975.

[5] P. M. Helfman and J. L. Bada, Nature, Volume 262, p. 279, 1976.

[6] P. M. Masters, J. L. Bada and J. S. Zigler Jr, Nature Volume 268, p. 71, 1977.

[7] P. M. Masters, J. L. Bada and J. S. Zigler Jr, Proc. Nat. Acad. Sci. USA, Volume 75, p. 1204, 1978.

[8] W. H. Garner and A. Spector, Proc. Nat. Acad. Sci. USA, Volume 75, p. 3618, 1978.

[9] P. N. Mcfadden and S. Clarke, Proc. Nat. Acad. Sci. USA, Volume 79, p. 2460, 1982.

[10] J. H. Jensen and M. S. Gordon, J. Am. Che.m Soc. Volume 117, p. 8159, 1995.

[11] M. Briget Mary, V. Ramakrishnan, Spectrochimica Acta A, Volume 62, p. 164, 2005.

[12] Peter I. Nagy and Bela Noszal, J. Phys. Chem. A Volume 104, p. 6834, 2000.

[13] J. T. Lopez Navarrete, V. Hernandez and F. J. Ramirez, J. Mol. Str. Volume 348, p. 249, 1995.

[14] P. Wang, I. Ando, J. Mol. Str., Volume 508, p. 103, 1999.[15] Peter I.Nagy and Belanoszal, Spectarochimica Acta part A,

Volume 104(29), pp. 6834-6843, 2000.[16] Z. Pászti , L. Guczi , Vibrational Spectroscopy, Volume 50(1),

pp. 48-56, 2009.[17] Michał H. Jamróz, Spectarochimica Acta, part A, Volume 114,

pp. 220-230, 2013.

Dr. Santosh Kumar is currently working as Associate Professor in the Department of applied sciences, IEC College of Engineering and Technology Gr. Noida. Obtained MSc from VBSPU University, Jaunpur in1994 and PhD from BHU in 2006. Published over dozen papers in international and national journals. He is also an author of a book with title “Vibrational Spectroscopy of Some Biomolecules”, VDM Publishers, Germany. Presently he is working in the area of laser spectroscopy and its applications.

AKGEC

Ajay Kumar Garg Engineering College

Invitation for Manuscripts concerning engineering subjects for publication in the AKGEC International Journal of Technology.

In tune with its innovative leadership in academics, Ajay Kumar Garg Engineering College, Ghaziabad is commencing publication of a Technical Journal to provide a forum for publishing new findings on engineering and technology.

AKGEC International Journal of Technology with a periodicity of six months is distributed among top-level universities and technical institutions worldwide with no charge, so that it may encourage further development in the related fields. All communications in this respect will be free of cost.

The idea behind this task is to provide platform that encourages innovations in the field of engineering and make exchange of the same among other institutions of repute abroad. This effort would certainly help the growth of research and its subsequent expeditious progress in the world.

Scientific articles are invited from faculty members and scientists related to engineering branches, namely, Electrical Engineering, Electronics, Communication Technology, Instrumentation and Measurement, Information Technology, Computers, Mechanical Engineering, Robotics and allied disciplines.

SUBMISSION GUIDELINES: Soft copies of the articles generally, limited to 3000 words in Word format are invited. IEEE style of preparation of the manuscript will be followed. The main article be preceded by 200-words abstract highlighting major findings. Equations should be composed using ‘Equations Editor’. They should not be pdf images.

Figure captions should not form part of the figures: they should be composed separately at the bottom of each figure. Photographs should have adequate contrast. Line diagrams and graphs should have clear labels and self-explanatory captions. Tables should be serially-numbered and put together at the end. Their Titles should be composed in capitals and positioned at the top of respective Table.

Each reference must be cited within the text matter and composed as per the IEEE style. Examples:

(i) For Journals: Akhilesh Tyagi, “A Reduced-Area Scheme for Carry-Select Adders”, IEEE Trans. Computers, Volume 42, No. 10, 1990, pp. 1163-1170.

(ii) For Books: E. A. Brandes and G. B. Brook, Smithells Metals Reference Book, 1992, Oxford, Butterworth Heinemann, pp.200-205.

(iii) Conference Proceedings: Du Lingling, “Study on Supercapacitor Equivalent Circuit Model for Power Electronics Applications”, Proc. 2nd International Conference on Power Electronics and Intelligent Transportation System, 2009, pp 51-54.

Contributions may please be e-mailed to: [email protected]

Call for Manuscripts

ANNOUNCEMENT

AKGEC

AKGEC International Journal of Technology

Management of Ajay Kumar Garg Engineering College deeply appreciates the time

and effort involved in preparation, submission, blind peer-review and publication of

technical articles. Since last six years, the College has taken a landmark lead in this

frontier that requires passionate dedication to achieve audacious goals.

Since its inception, the journal has published 143 articles, contributed by authors in

India and abroad. Accolades received from professional fraternity reinforce our

resolve to forge further in this task.

We wish to celebrate the seventh Anniversary of this effort via an epochal

announcement.

To recognize the invaluable Intellectual contribution made by professionals in

advancing the noble cause of dissemination of scientific and engineering knowledge,

all published articles in Volume 7 of the “AKGEC International Journal of Technology”

will be suitably rewarded.

A prize of 5,000 will be paid to the paper adjudged the best for each issue. For the

balance, an amount of 2,500 per article is earmarked.

In tune with the spirit of ‘Digital India’, the Honorarium will be electronically credited

to authors’ saving bank account. In response to our communication of acceptance of

the manuscripts, the author will be expected to provide bank-details in a prescribed

format to facilitate this task.

Please take a moment to evaluate the articles you have read in this issue of “AKGEC International Journal of Technology”, Volume 7, No. 1, January-June 2016. Your valuable comments will help us shape the future issues better. Thank you!

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Pre Bond Through Silicon Vias (TSVs) Testing in 3D ICsAbdul Manan

Hybridisation of PTS-Clipping Techniques to Progress PAPR in MIMO-OFDM SystemsRaj Lakshmi Shukla and Monika Singh

Electricity Generation due to Vibration by BootsVaibhav Sharma and Mohini Preetam Singh

Kinematic Modeling of a Multi-Fingered Robotic Hand- A ReviewM.Z. Hussain and Dr. M. Suhaib

Overview on Burr Formation, Simulation and Experimental Investigation of Burr size - based on Taguchi Design of Experiments during Drilling of Alluminium 7075 Alloy Reddy Sreenivasulu and Chalamalasetti Srinivasa Rao

An Empirical Investigation of the Various Antecedents of the Customer Satisfaction in Case of Mobile Services - A Comprehensive Study of Haryana Province in India Vishal Garg

Design Optimization of IC Engine Rocker-Arm Using Taguchi Based Design of ExperimentsDr. Goteti Chaitanya and Reddy Sreenivasulu

Latest Trends in CommunicationsManjit Singh

Factors Influencing the Adoption of Internet Banking in Selected Banks of Ethiopia - A Study Dr. Girish Kumar Painoli

Vibrational study of Aspartic AcidsDr. Santosh Kumar

ToEDITOR AKGEC International Journal of TechnologyAjay Kumar Garg Engineering College27th Km Stone, Delhi-Hapur Bypass Road, PO Adhyatmik Nagar, Ghaziabad 201009 (U.P.) India

ToEDITOR AKGEC International Journal of TechnologyAjay Kumar Garg Engineering College27th Km Stone, Delhi-Hapur Bypass Road, PO Adhyatmik Nagar, Ghaziabad 201009 (U.P.) India

journal jan-june 2016

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