pkh report
TRANSCRIPT
-
8/8/2019 PKH Report
1/40
CHAPTER 1
INTRODUCTION
1.1. GENERAL
Development of machine tools forms the basis of the industrial
improvement and has been realized especially better accuracy of machined
parts. Turning is the most widely used among all turning operations is gaining
new dimensions in the present industrial age, in which the growing competition
calls for all the efforts to be directed towards the economical manufacture of
machined parts and surface finish is one of the most critical quality measure in
mechanical products as the competition grows closer, customer now have
increasingly high demands on the quality, making surface roughness one of the
quality, making surface roughness one of the most competitive parameters in
todays manufacturing industry. The quality of machined component is evaluated
by how closely they adhere to set product specifications of length, width, surface
finish etc. Among them surface finish is the central to determining the quality of
workspace. In practice, predicting and controlling the roughness is difficult, which
due to the fact that many variables are affecting the process. Some of these
factors can be controlled and some cannot. Controllable process parameter
include feed, cutting speed, tool geometry and tool setup.
The development within production engineering is accompanied by
increasing quality requirements of the produced work pieces. It is important to
limit vibrations of the machine tool structure as their presence results in poor
surface finish, cutting edge damage, and irritating noise. The causes and control
of free and forced vibrations are generally well understood and the sources of
vibration can be removed or avoided during operation of the machine. Chattervibrations are less easily controlled and metal removal rates are frequently
limited because the operator must stop the machine to improve the machining
conditions, which often means reducing the depth of cut of feed rate. In the
previous researches the steel with less hardness is taken as work piece and the
1
-
8/8/2019 PKH Report
2/40
experiment is conducted for that work piece, but in this study OHNS (oil
hardened non-shrinkage steel) of hardness 45HRC is taken for the experiment.
Machining parameters affects production rate, quality and cost of a
product. The selection of machining parameters is traditionally carried out by
process planners rather on the basis of their experience or with the help of
machining database. However, the parameters selected by such practice do not
include any economic criterion in a machining process will usually be either to
minimize the production cost or maximize the production rate. Moreover, in
determining the optimal parameters, special attention has to be give to the
constraints imposed on the production operation by machine tools, cutting tool
and work piece.
The challenge of modern machining industries is mainly focused on the
achievement of high quality in terms of work piece, dimensional accuracy,
surface finish, high production rate, less wear on cutting tool, economy of
machining in terms of cost saving and increase the performance of the product
with reduced environmental impact.
1.2. Chatter Vibrations and Damping
The basic cause of chatter is the dynamic interaction of the cuttingprocess and the machine tool structure. During cutting, a force is generated
between the tool and work piece, which acts at an angle to the surface. The
magnitude of this cutting force depends largely on the tool-work engagement and
depth of cut. The cutting force strains the structure elastically and can cause a
relative displacement of the tool and work piece, which alters the tool-work
engagement (un-deformed chip thickness). Chatter is the resonant vibration of
cutting or work piece. The produces the following effects,
1. It increases wear of cutting tool and machine tool
2. Vibration of the machine tool work piece system deteriotes the surface
finish and accuracy.
3. It reduces tool life.
2
-
8/8/2019 PKH Report
3/40
1.3. Elimination of chatter
It is desirable to reduce chatter in order to improve work piece surface
finish and to protect the machine tool. Self excited vibration are more severe and
has the forced vibrations. Chatter can be reduced by the following methods.
1. Chatter can be reduced by the use of special device such as vibration
dampers which impede the development of vibrations work piece system.
2. Rigid installation of machine tool on its properly prepared foundation
reduces the vibrations.
3. The use of cutting fluids sometimes helps to reduce vibrations.
4. The machine tool should be dynamically balanced to limit the unbalanced
forces produced during its operation.
1.4. Effect of vibration on the cutting conditions
There are mainly three effects on the cutting conditions
1. Chip thickness variation effect.
2. Penetration rate variation effect.
3. Cutting speed variation effect.
1.5. Hard Turning
Hard turning is a cutting process defined as turning materials with
hardness higher than 45 HRC under appropriate cutting tools and high cutting
speed. Machining of hard steel using advanced tool materials, such as mixed
ceramic, has more advantages than grinding or polishing, such as short cycle
time, process flexibility, compatible surface roughness, higher material removal
rate and less environment problems without the use of cutting fluid. High-speed
machining of dies and molds in their hardened state has become a normal
practice in industry because it increased productivity and reduced energy
consumption.
Hard turning is a cost- effective, high productivity and flexible machining
process for ferrous metal work pieces that are often hardened above 40 HRC
3
-
8/8/2019 PKH Report
4/40
and up to 60 HRC. This process has become a popular technique in
manufacturing of gears, shafts, bearings, cams, forgings, dies and molds. Hard
machining is performed dry using ceramics and polycrystalline cubic boron nitride
(PCBN, commonly CBN) cutting tools due to the required tool material hardness.
Hard turning is a lathe machining process where most of the cutting is done with
the nose of the inserts.
In addition to the effects of work material hardness, tool geometry and
cutting conditions on surface integrity of the finish machined parts. Since hard
turning demands a strong and prudent tool cutting edge, nose design with proper
edge preparation becomes crucial to provide high edge strength as well as to
attain favorable surface roughness. Performance of Ceramic and CBN cutting
tools and the quality of the surfaces machined are highly dependent on cut and
the tool nose radius which significantly influence surface roughness.
1.6. Need for the research
Extensive research has been devoted to the characterization, modeling,
and control of vibrations that occur when machine tools operate at the limit of
their dynamic stability. These vibrations, known as machine-tool chatter, must beavoided to maintain machining tolerances, preserve surface finish, and prevent
tool breakage. To avoid chatter, machine tool users limit material removal rates
in order to stay within the dynamic stability boundary of their machines. From a
manufacturing stand point, chatter is a constraint on the machine-tool user that
limits the available production capacity. Thus, vibration-control methods for
extending machine-tool operating envelopes are highly desirable.
1.8. Objective of the research
1. To determine the vibration spectrum curve using vibration data
collector for various overhanging length of boring bar and also by
varying the speed, feed under dynamic condition .
4
-
8/8/2019 PKH Report
5/40
CHAPTER 2
LITERATURE REVIEW
2.1. Vibration
L.Petterson, L.Hakanson, I. Claesson, and S. Olsson states that the
knowledge of vibrations involved in boring operations and active control of
external turning operations, have given a good basis for the active control
solution in boring operations. The active control solution is based on a standard
boring bar with an embedded piezo ceramic actuator placed at the peak modal
strain of the boring bar. An accelerometer is also included in the design, mounted
as close as possible to the cutting tool. The control algorithm is a filtered X LMS
algorithm built on a feedback approach since the original excitation, the cutting
process, cannot be observed directly. Preliminary results show reduction of the
vibration in the boring bar by up to 30db.
Damping capacity greatly affects the dynamic rigidity of a machine tool
system. This paper deals with the damping capacity of boring tools. Dampingcapacity is measured as a function of clamping conditions such as clamping
conditions such as clamping load or surface topography of tool shank. An
empirical equation of damping capacity representing the clamping load
dependence is induced for the fundamental mode of vibration in tangential and
normal directions. The optimum clamping load, at which the stability of turning
tool for chatter excitation becomes maximum, is experimentally clarified [2].
Y.Altintas,E.Budak presents a new method for the analytical prediction of
stability lobes in milling. The stability model requires transfer function of the
structure at the cutter-work piece contact zone, static cutting force coefficients,
radial immersion and the number of teeth on the cutter. Time varying dynamic
cutting force coefficients are approximated by their Fourier series components
5
-
8/8/2019 PKH Report
6/40
and their chatter free axial depth of cuts and spindle speeds are calculated
directly from the proposed set of linear analytical expressions without any digital
iteration. Analytically predicated stability lobes generated by time domain and
another numerical methods available in the literature.
Fedrico M. Anerio, Reginaldo T. Coelho, Lincoln C.Brandao the efficiency
of the high-speed milling process is often limited by the occurrence of chatter. In
order to predict the occurrence of chatter, accurate models are necessary. In
most models regarding milling the cutter is assumed to follow a circular tooth
path. However the real tool path is trochoidal in the ideal case, i.e., without
vibrations of the tool. Therefore, models using a circular tool path lead to errors,
especially when the cutting angle is close to 0 or radians. An updated model
for the milling process is presented which features a model of the unreformed
chip thickness and a time-periodic delay. In combination with this tool path
model, a nonlinear cutting force model is used; to include the dependency of the
chatter boundary on the feed rate. The stability of the milling system, and hence
the occurrence of chatter, is investigated using both the traditional and the
trochoidal model by means of the semi-discrimination method. Due to the
combation of this updated tool path model with a nonlinear cutting force model,the periodic solution of this system, representing a chatter-free process, needs to
be computed before the stability can be investigated. This periodic solution is
computed using a finite difference method for delay- differential equations.
Especially for low immersion cuts, the stability lobes diagram (SLD) using the
updated model shows significant differences compared to the SLD using the
traditional model. Also the use of the nonlinear cutting force model results in
significant differences in the SLD compared to the linear cutting force model. [4]
Xiaolio Li, Alexander Djordjevich, and Patri K. Venuvinod in this part of
the paper series, chatter experiments are conducted in order to verify the
proposed stability models presented in the first part. Turning and boring chatter
experiments are conducted for the cases where the tool or the work piece is the
6
-
8/8/2019 PKH Report
7/40
most flexible component of the cutting system. In addition, chatter experiments
demonstrating the effect of the insert nose radius on the stability limit are
presented. Satisfactory agreements is observed between the analytical
predictions and the experimental results.[5]
Mohammed Usman Ghani-Nuri A.Abukshim, presents a new method for
varying the spindle speed to suppress chatter in machining. The spindle speed is
varied in a pseudo-random fashion within the bandwidth of the spindle system.
Both implementation issues and spindle system responses to such signals are
investigated. A new method to analyze the stability of machining systems with
varying spindle speed is also introduced. The effectiveness and advantages of
the random spindle speed variation in chatter suppression is verified using
numerical simulations and experiments.
Jing Shi, C.Richard Liu A finite modal is developed to predict the chip formation
and phase transformation in orthogonal machining of hardened AISI 52100 steel
(62HRC) using Poly crystalline Cubic Boron Nitride(PCBN) tools. The model
mainly includes a chip separation criterion based on critical equivalent. Plastic
strain; a coloumbs law for the friction at the tool/chip interface; a thermal analysisincorporating the heat dissipated from inelastic deformation energy and friction;
and an annealing effect model, in which the work hardening effect may be lost or
re-accumulate depending on material temperature. This fully coupled thermal
mechanical finite element analysis accurately simulates the formation of
segmental chips, as verified by experiment. It is found that high temperature
around the secondary shear zone causes fast re-austenitization and martensite
transformation, while other parts of the chips retain the original tempered
martensite structure.
7
-
8/8/2019 PKH Report
8/40
2.2 Signal Processing
Quality evaluation and control is an almost universal concern in across all
manufacturing sectors. Statistical methods play an important role, as do both
automated and human inspection. Many sensing modalities including electrical
physical, optical, x-ray, acoustical, ultrasound, chemical measurements (M.P.S.
Krishnan Kiran et al., 2007) applied in inspection procedures; many of these
measurements already contain, or could be enchanced by, signal conditioning
and machine monitoring applications. These include auto-regressive (AR)
models, time domain signal envelope analysis and other time-domain methods
such as kurtosis or root-mean-square (RMS) signal power (Alexandria, VA 1996).
The constant false alarm rate (CFAR), ratio of power (ROP), Kurtosis and
correlation of AE have been presented more sensitive than root mean square
(RMS) (Paulo R.Aguiar et al., 2006).
Many paper described the practical aspect of vibration phenomena and
measurement requirements of a general monitoring system consisting of data
collection with data reports in digital manner, followed by the acquisition phase
calculating the statistical values and functions in time and frequency domain withintergrated data reduction by fault and operational pattern (Wilfried Reimche et
al., 2003; Warren Liao T et al., 2007; Steven Y. Liang et al., 2004). AE RMS
frequency and count rate have good correlation with white layer formation and
thus, may be used to monitor surface integrity factors (Guo. Y.B. et al., 2005).
The tool wear forms were correlated to features in the vibrations signals in the
time and frequency domains (Dimla D,E 2002). Signal parameters characterizing
acoustic emission (AE) detected during metal cutting have been theoretically
correlated in a simple manner, to the work material properties, cutting conditions
and tool geometry (Keraita J.N. et al 2000 and Richard Y. Chiou et al., 2000).
Arnuad and Devillez (2006) were discussed the problem of vibration occurring
during a machining operation and signals of tool micro movement were
8
-
8/8/2019 PKH Report
9/40
correlated with surface finish. Surface roughness has received serious attentions
for many years.
A considerable number of studies have been investigated the general
effects of the speed, feed, and depth of cut, nose radius and others on the
surface roughness. In the present paper, the effects of carbide shim, Brass, shim
and Aluminum shin on surface roughness in turning process are also studies.
Vibration signal are collected using accelerometer during machining process for
different dampers. The surface roughness of the machined workpieces is
measured using surface tester. Features of the amplitude spectrum and
probability density curve are correlated with the measured roughness values.
9
-
8/8/2019 PKH Report
10/40
CHAPTER 3
METHODOLOGY
Based on the literature review and an examination of prior experimentalstudies, a methodology was developed to study the progression of flank wear of
the cutting tools and the change in the surface roughness of the machined part in
turning. Since the present trend in the manufacturing industry is high speed dry
machining. It was suggested to apply dry machining and high turning speed to
simulate the machining conditions that are observed to typical manufacturing
industries. This chapter describes the steps that were taken to achieve the
objectives of this study Commercially available cutting tools that are used by
numerous manufacturing Industries were ordered from cutting tools distributors,
and the appropriate machining parameter were selected so that the machining
experiment would simulate the conditions in the manufacturing industry.
3.1 MACHINE SELECTION:
Machine : MAS CENTER LATHE
Make : ACE Designers (Bangalore)
Work piece
Materials : OHNS AISI 01
Composition : (C=0.90%, Cr=.50%, Mn=1.00%,
W=0.5%, Hardness=45 HRC
Size : 120mm length and 30mm diameter.
Cutting tool
Cutting insert: Carbide, CNMG 120408 (P-30 ISO specification)
10
-
8/8/2019 PKH Report
11/40
INSERTVIEW
Fig.1. PVD miracle coating
Tool holder: PSBNR 2525M12(ISO specification),
Working tool geometry: -6,-6, 6, 6, 15, 75
Cutting Condition :
Cutting Speed : 1000rpm, 600 rpm
Feed : 0.31 mm/rev, 0.17 mm/rev
Depth of Cut : 0.5mm, 1.0mm
11
-
8/8/2019 PKH Report
12/40
3.2. EXPERIMENTAL CONDITION
Ex. No CUTTING SPEED (rpm) FEED(mm/rev) DEPTH OF CUT (mm)
EX 1 1000 0.34 1
EX 2 1000 0.34 0.5
EX 3 1000 0.17 1
EX 4 1000 0.17 0.5
EX 5 600 0.34 1
EX 6 600 0.34 0.5
EX 7 600 0.17 1
EX 8 600 0.17 0.5
Table .1
12
-
8/8/2019 PKH Report
13/40
3.3. ONLINE MONITORING INSTRUMENTS
3.3.1 ACCELEROMETER:
Type : SENDIG L-15 Accelerometer
An accelerometer is a liner seismic transducer which produces an
electric charge proportional to the applied acceleration. A simple model of an
accelerometer is shown in fig 2. a mass is supported on a piece of piezoelectric
ceramic crystal which is fastened to the frame of the transducer body.
Piezoelectric materials have the property that if they are compressed or shared,
they produce an electric potential between their extremities.
Fig.2. Accelerometer Setup
Specifications:
Sensor: Charge-output Accelerometer
Output: 0-5Vdc or 4-20mAdc, True RMS, Equivalent Peak, Equivalent Peak-
Peak,
13
-
8/8/2019 PKH Report
14/40
Overall value output Displacement, Velocity, Acceleration
Waveform Output: +5Vac, Displacement, Velocity, Acceleration all are
voltage can be observed by using oscillograph or spectrum
analyzer.
Alarm output : TTL signal, 1 level adjustable
Electrical power isolation to reduce ground disturbance
This electric potential is proportional to the amount of compression or
shear. As the frame experience an upward acceleration it also experiences a
displacement. Because the mass is attached to the frame through the spring-like
piezoelectric element, the resulting displacement it experiences is of different
phase and amplitude than the displacement of the frame. This relative
displacement between the frame and mass causes the piezoelectric crystal to be
compressed, giving off a voltage proportional to the acceleration of the frame
3.3.2. Vibration Collector
A simple model of an vibration data collector is shown in fig 3. Vibration
data collector, It can be used in field vibration measurement, fault analysis,machinery condition monitoring as well as the storage of the characteristic values
and waveforms of acceleration
14
-
8/8/2019 PKH Report
15/40
Fig.3. Vibration Collector
The velocity, displacement and high-frequency acceleration envelope. Its
measurement data can be sent to a computer for archiving of equipment
maintenance information database and signal analysis and fault analysis.
3.3.3. MCME 2.0H SOFTWARE
Sendig-900 is aseries of instrument that used for condition monitoring and
faults diagnosis of machinery.
This program provides a variety of tools and technologies to make your
manipulation of Sendig-900 even easier and more efficient. It constructs a
database system to store and manage the vibration information that collected
from spots, which solved successfully the matter of memory lack. Powerful
graphics display and data processing function can show the vibration waveforms
and spectrum that stored in the files. Through calling the fault diagnosis expert
system, it can instruct the causes of faults and means of maintenance
15
-
8/8/2019 PKH Report
16/40
3.3.5.ONLINE EXPERIMENTAL SETUP:
The Experimental setup consists of an accelerometer and vibration data
collector. the details of cutting tests are given in the table 1. In the first
experimental group 8 experiments were carried out using 2 and for each shim.
Fig. 5. Experimental setup
16
-
8/8/2019 PKH Report
17/40
Two different cutting conditions were selected. Each work piece is 120mm
length and 30mm diameter. A commercial piezoelectric sensor of Beijing
SENDIG Technology Co was mounted on the top of the tool holder using a
magnet ring fixture. The sensor was placed as close as possible to the cutting
insert to minimize signal loss and achieve a good signal-to-noise ratio.
Fig.6. Online Experimental setup
Data base were created to collect signal up to 500Hz frequency spanusing MCMe2.0 software package of SENDIG and the data base were
transferred to vibration data collector before machining. The signals were
collected by vibration data collector 911 through the piezoelectric sensor during
the cutting test. After machining the collected vibration data and signals were
uploaded to software package MCMe2.0H.
17
-
8/8/2019 PKH Report
18/40
CHAPTER 4
RESULTS AND DISCUSSION
4.1. Experimental Analysis:
After the machining RMS value was measured using probability density
curve and average roughness value was measured using SJ400 surface
roughness tester .The average roughness value Ra is the most commenly used
parameter in surface finish measurement .
EXPERIMENT 1
AMPLITUDE SPECTRUM CURVE
18
-
8/8/2019 PKH Report
19/40
Graph. 1
PROBABILITY DENSITY CURVE
Graph. 1
Table. 2
19
RegionNatural frequency Ra
(m)RMS
Peak(amplitude) Frequency(Hz)
1
2
3
0.78
0.05
0.10
2.5
450
925
1.96 0.71
-
8/8/2019 PKH Report
20/40
From the graph 1 and table 2, it is observed that the third natural
frequency is greater than second natural frequency. At this time, the peak value
increases from second to third region. So chatter will occur.
EXPERIMENT 2
AMPLITUDE SPECTRUM CURVE
Graph. 2
20
-
8/8/2019 PKH Report
21/40
PROBABILITY DENSITY CURVE
Graph. 2
21
RegionNatural frequency Ra
(m)RMS
Peak(amplitude) Frequency(Hz)
1
2
3
0.51
0.08
0.07
5.0
495
1000
1.12 0.66
-
8/8/2019 PKH Report
22/40
Table. 3
From the graph 2 and table 3 value it is observed the second natural
frequency is less than third natural frequency. At this time, the second peak value
increases to the peak value decreases. So the curve diminishes, and chatter will
not occur.
EXPERIMENT 3
AMPLITUDE SPECTRUM CURVE
Graph . 3
PROBABILITY DENSITY CURVE
22
-
8/8/2019 PKH Report
23/40
Graph. 3
Table .4
From the graph 3 and table 4 value, it is observed the second natural
frequency is less than third natural frequency. At this time, the second peak
23
RegionNatural frequency Ra
(m)RMS
Peak(amplitude) Frequency(Hz)
1
2
3
0.61
0.12
below 0.5
7.5
475
900
1.01 0.66
-
8/8/2019 PKH Report
24/40
value increases to the peak value decreases. So the curve diminishes, and
chatter will not occur
EXPERIMENT 4
AMPLITUDE SPECTRUM CURVE
Graph .
4
PROBABILITY DENSITY CURVE
24
-
8/8/2019 PKH Report
25/40
Graph . 4
Table. 5
25
RegionNatural frequency Ra
(m)RMS
Peak(amplitude) Frequency(Hz)
1
23
0.51
0.040.06
7.5
435842.5
1.4 0.38
-
8/8/2019 PKH Report
26/40
From the graph 4 and table 5, it is observed that the third natural
frequency is greater than second natural frequency. At this time, the peak value
increases from second to third region. So chatter will occur.
EXPERIMENT 5
AMPLITUDE SPECTRUM CURVE
Graph. 5
26
-
8/8/2019 PKH Report
27/40
PROBABILITY DENSITY CURVE
Graph .5
Table .6
27
Region Natural frequency Ra(m)
RMSPeak(amplitude) Frequency(Hz)
1
2
3
0.77
0.06
0.08
5.0
445.0
887.0
1.31 0.59
-
8/8/2019 PKH Report
28/40
From the graph 5 and table 6, it is observed that the third natural
frequency is greater than second natural frequency. At this time, the peak value
increases from second to third region. So chatter will occur.
EXPERIMENT 6
AMPLITUDE SPECTRUM CURVE
Graph. 6
28
-
8/8/2019 PKH Report
29/40
PROBABILITY DENSITY CURVE
Graph. 6
29
RegionNatural frequency Ra(m
)RMS
Peak(amplitude) Frequency(Hz)
1
2
3
0.42
0.16
0.07
2.5
370.0
725
0.89 0.57
-
8/8/2019 PKH Report
30/40
Table. 7
From the graph 6 and table 7 value, it is observed the second natural
frequency is less than third natural frequency. At this time, the second peak value
increases to the peak value decreases. So the curve diminishes, and chatter will
not occur.
EXPERIMENT 7
AMPLITUDE SPECTRUM CURVE
Graph. 7
PROBABILITY DENSITY CURVE
30
-
8/8/2019 PKH Report
31/40
Table .8
From the graph 7 and table 8 value, it is observed the second natural
frequency is less than third natural frequency. At this time, the second peak value
increases to the peak value decreases. So the curve diminishes, and chatter will
not occur
EXPERIMENT 8
AMPLITUDE SPECTRUM CURVE
31
Region Natural frequency Ra
(m)
RMS
Peak(amplitude) Frequency(Hz)
1
2
3
0.28
0.15
0.07
7.5
460
477.5
0.9 0.40
-
8/8/2019 PKH Report
32/40
Graph. 8
PROBABILITY DENSITY CURVE
32
-
8/8/2019 PKH Report
33/40
Graph .8
Table. 9
From the graph 8 and table 9 value, it is observed the second natural
frequency is less than third natural frequency. At this time, the second peak value
33
RegionNatural frequency Ra
(m)RMS
Peak(amplitude) Frequency(Hz)
1
2
3
1.0
0.06
0.05
5.0
730
807.5
0.90 0.69
-
8/8/2019 PKH Report
34/40
increases to the peak value decreases. So the curve diminishes, and chatter will
not occur.
4.2. COMPARISON OF OFFLINE AND ONLINE SYSTEM
SURFACE ROUGHNESS VALUE AND RMS VALUE
Ex. NoCUTTING
SPEED(rpm)FEED(mm/rev)
DEPTH OF
CUT (mm)Ra (m) RMS
EX1 1000 0.34 1 1.96 0.71
EX2 1000 0.34 0.5 1.12 0.66
EX3 1000 0.17 1 1.01 0.66
EX4 1000 0.17 0.5 1.4 0.38
EX5 600 0.34 1.41 1.31 0.59
EX6 600 0.34 0.5 0.57 0.89
EX7 600 0.17 1 0.9 0.40
EX8 600 0.17 0.5 0.903 0.69
Table.10
From the table 10 when the cutting speed and depth of cut increase
corresponding to the roughness value and RMS value increases. So chatter will
occur.
When the cutting speed and depth of cut decrease corresponding to
the roughness value and RMS value decrease. So chatter will occurs.
34
-
8/8/2019 PKH Report
35/40
4.3.CONCLUSION CHART
E.NO
Natural
frequencyFrequency(HZ
)RMS Ra (m) Remarks
EX1
1 0.78
2 0.05
3 0.10
2.5
450
925
0.71 1.96 Chatter
EX2
1 0.51
2 0.08
3 0.07
5.0
495
1000
0.66 1.12 No Chatter
EX3
1 0.61
2 0.12
3 900
7.5
4.75
below 0.5
0.66 1.01 No Chatter
EX4
1 0.51
2 0.04
3 0.06
7.5
435
842.5
0.38 1.4 Chatter
EX5
1 0.77
2 0.06
3 0.08
5.0
445.0
887.0
0.59 1.31 Chatter
EX6
1 0.42
2 0.16
3 0.07
2.5
370.0
725
0.89 0.57 No Chatter
EX7
1 0.28
2 0.15
3 0.07
7.5
460
477.5
0.40 0.9 No Chatter
EX81 1.02 0.06
3 0.05
5.0730
807.5
0.69 0.903 No Chatter
Table.11
35
-
8/8/2019 PKH Report
36/40
CHAPTER 5
CONCLUSION
The following observation is made by introducing signal analysis method for
online monitoring of the chatter and surface roughness. The dynamic
characteristics for hard turning of OHNS01 material with various cutting speed
are investigating by using vibration data collector and surface roughness tester
1. The third natural frequency is greater than second natural frequency. At
this time, the peak value increases from second to third region. So chatter
will occur.
2. The second natural frequency is less than third natural frequency. At this
time, the second peak value increases to the peak value decreases. So
the curve diminishes, and chatter will not occur.
3. When the cutting speed and depth of cut increase corresponding to the
roughness value and RMS value increases. So chatter will occur.
4. When the cutting speed and depth of cut decreases corresponding to the
roughness value and RMS value decreases. So chatter will occurs.
36
-
8/8/2019 PKH Report
37/40
BIOBLIOGRAPHY
1.E.Marui, M. Hashimoto, and S. Kato, 1993, Damping Capacity of Turning
Tools, Part- 1; Effect of Clamping Conditions and Optimum Clamping Load,
JOURNAL OF ENGINEERING FOR INDUSTRY, Vol. 115, pp 362-366.
2.S. D. Yu, V. Shah, 2008 Theoretical and Experimental Studies of Chatter in
Turning for Uniform and Stepped Workpieces, Journal of Vibration and
Acoustics, Vol. 130, pp 061005- (1-18).
3.Alpay Yilmaz, Emad AL-Regib and Jun Ni, 2002, Machine Tool Chatter
Suppression by Multi-Level Random Spindle Speed Variation, Journal of
Manufacturing Science and Engineering, ASME, Vol. 124,pp 208-216.
4.R.P.H. Faassen, N. Van de Wouw, H. Nijmeijer, J. A.J. Oosterling, 2007. An
Improved Tool Path Model including Periodic Delay for Chatter Prediction in
Milling, journal of Computational and Nonlinear Dynamics, Vol.2, pp 167-179.
5.Emre Ozlu, Erhan Budak, 2007 Analytical Modeling of Chatter Stability in
Turning and Boring Operations-Part II; Experimental Verification, journal of
Manufacturin Science and Engineering, ASME, Vol, 129, pp 733-739.
6.Alpay Yilmaz, Emad Al-Regib, Jun Ni, 2002, Machine Tool Chatter
Suppression by Multi-Level Random Spindle Speed Variation, JOURNAL OF
MANUFACTURING SCIENCE AND ENGINEERING ., Vol. 124, pp 208-216.
37
-
8/8/2019 PKH Report
38/40
7.M. A. Elbestawi, F. Ismail, B.C. Ullagaddi, 1994, Modelling Machining
Dynamics Including Damping in the Tool-Workpiece interface, journal of
Engineering for Industry, Vol. 116, pp 435-439.
8.Ty G. Dawson, Thomas R. Kurfess, 2006, Modeling the progression of Flank
Wear on Uncoated and ceramic-Coated Polycrystalline Cubic Boron Nitride Tools
in Hard Turning, journal of Manufacturing Science and Engineering, ASME,
Vol.128, pp 104-109.
9.Yoshitaka Morimoto, Yoshio Ichida, Ryunosuke Sato and Tomoyuki Hoshi,
2003, Vibration Control of On Nc Lathe Frequency Damper SICE annual
conference in fukui, page 2961-2966.
10.T.Alwarsamy, P. Thangavel, V. Selladurai, 2007, Reduction of Machining
Vibration By Use of Rubber laminated Between laminates Between Tool Holder
and Insert, Machining Science And Technology, page 11:135-143.
11.Conor D. Johnson, David A. Kienholz, 1982, Finite Element Prediction of
Damping in Structure with Constrained Viscoelastic Layers. AIAA Journal, Vol-20, no.9,pp 1284-1290
12.Conor D. Johnson, 1984, Passive Damping Technology Using Viscoelastic
Geoffrey P. Mc Knight, Greg P. Carman Energy Absorption in Axizl and Shear
Loading of Particulate Magnetostrictive Composites.
13.Zhiwei Xu, Micheal Yu Wang, Tianning Chen, 2003, Particle Damping for
Passive Vibration Suppression : Numerical Modeling With Experimental
Verification, ASME.
38
-
8/8/2019 PKH Report
39/40
-
8/8/2019 PKH Report
40/40
21.Hassui A. and Diniz A.E, (2003) Correlating surface roughness and vibration
on plunge cylindrical grinding of steel, International journal of Machine Tools and
Manufacturing, Vol.4., No.8, pp 855-862.
22.George Balan (1996), New Results in the Study of Machine Tools
Vibrations Part 1: Critique look on a Current state in the Study of Chatter
Phenomenon FASCICULA V, Dunarea de jos, Galati University ISSN 1221-
4566, pp.21-24.
23.Ghani A.K., Choudhury I.A. and Husni, (2003) Study of the tool life
roughness and vibration in machining nodular cast iron with Carbide tool, journal
of material processing and technology, Vol.127, No.1, pp. 17-22.
24.Guo Y.B and Ammula S.C., (20050 Real-time acoustic emission monitoring
for surface damage in hard machining, International journal of Machine tools &
manufacture, Vol.45, pp.1622-1627.
25.Joseph C. Chen, luke H.Huang , Ashley X.Lan and Samson Lee (1999)
Analysis of an effective Sensing Location for an In-process surface recognition
system in turning Operations, journal of Industrial technology, Vol.15, No.3,
pp.1-6.
26.Julie Z.Zhang, Joseph Chen C., Danial Kirby E., (2007) Surface roughness
optimization in an end-milling operation using the Tauguchi design method,
Journal of material processing Technology, Vol.184,pp.233-239.