investigating the effect of machining parameters on ... · the final results are a database for...

BULETIN ŞTIINłIFIC, Seria C, Fascicola: Mecanică, Tribologie, Tehnologia ConstrucŃiilor de Maşini

SCIENTIFIC BULLETIN, Serie C, Fascicle: Mechanics, Tribology, Machine Manufacturing Technology

ISSN 1224-3264, Volume 2014 No.XXVIII

12

Investigating the Effect of Machining Parameters

on Surface Roughness of 7136 Aluminum Alloy in End Milling

Alina Bianca BONTIU POP 1*

Abstract: Surface quality is affected by different processing parameters and inherent uncertainties of the metal cutting

process. Thus, the anticipation of surface roughness becomes a real challenge for engineers and researchers. The

purpose of this paper is to study the 7136 aluminum alloy used in the aircraft industry, to obtain data for the effect of

the cutting feed on surface quality and manufacturing time reduction, in end milling operations using standard tools for

aluminum machining. The final results are a database for future research.

Keywords: Al 7136, surface roughness, end milling, aircraft industry.

1 INTRODUCTION

Surface roughness greatly influences the

performance of mechanical parts as well as production

cost, therefore, it is a very important measure of product

quality. Also, surface roughness has a great impact on

mechanical properties like fatigue behavior or corrosion

resistance and functional attributes like wear, friction,

light reflection, heat transmission, and electrical

conductivity.

Currently, there have been many research

developments in surface roughness modeling and

optimization of the metal cutting process parameters to

obtain a surface finish of desired level, since only the

proper selection of these parameters can produce a better

surface finish.

In the manufacturing industries, various

machining processes are adopted to get the higher

quality of products. Among these, the end milling

process is the one of the most significant and common

metal cutting operations used for machining parts

because of its ability to remove materials faster with a

reasonably good surface quality.

Surface roughness and dimensional accuracy

are significant factors in predicting the machining

performances of any machining operation.

2 REVIEW OF LITERATURE

Analyzing the research report [1] entitled

"Contributions and research on modeling and finite

element analysis of metal cutting tribosystem", in which

116 scientific papers were studied during 2000-2014, I

found some global aspects emerging from this research.

But, before specifying these aspects, I want to present

some of the scientific papers in which the research aim is

the surface quality of aluminum alloys.

The first of these papers is [2], in which Ghan

and Ambekar are studying the LM-26 aluminum alloy.

In [2], they seek to obtain optimal machining parameters

to achieve better surface finish characteristics during

milling, better material removal rate during turning, and

better or optimum machining time during turning. Also,

they performed an analysis using ANOVA and Taguchi

techniques, which are the cutting parameters with the

greatest influence on the surface roughness and on

reduction of manufacturing times.

Tamminen and Yedula in [8] are aimed to

optimize the surface quality of 1050 aluminum alloy in

end milling processes by anticipating the surface

roughness using RSM (Response Surface Methodology).

The experiment shows that the feed rate is a dominant

parameter and the surface roughness increases rapidly

with the increase in feed rate and decreases with increase

in cutting speed, where as the effect of depth of cut is not

regular [8].

Gulhane et al. in [3] tested the influence of the

cutting process parameters of Al6061 in end milling

operations, following the surface quality using Taguchi

and ANOVA statistical methods in order to obtain more

accurate results. The authors’ conclusion shows that feed

is the most influencing parameter corresponding to the

quality characteristics of surface roughness.

The effect on surface roughness of 6061

aluminum alloy was investigated by Kuttolamadom et al.

in [5], where these results were used to recommend

machining practices for improved surface quality and

hence minimizing cycle time, thus improving

productivity. Thus, the contribution of each parameter

was inferred, and a recipe prescribed (i.e. increase the

feed up until a cutoff surface roughness limit is reached

and then increase the surface speed within the roughness

range to maximize productivity).

The Al7075 analysis was approached by

Vakondios et al. in [9], who performed a number of

experiments testing different cutting conditions

including axial and radial depth of cut, feed rate, and

inclination angles. Regression analysis and analysis of

variance were performed during these experiments. The

outcome was to provide a series of mathematical models

for the determination of surface roughness (Rz) for each

of the milling strategies available (vertical, push, pull,

oblique, oblique push, and oblique pull milling). Both

climb and conventional milling were covered and thus

establish the influence of the milling strategy used to the

resulting surface roughness in ball end milling [9].

Kadirgama et al. in [4] discuss the surface

roughness optimization of Al6061 alloy, using RSM

(Response Surface Methodology) and RBFN (Radian

Basis Function Network) approaches by optimizing the

cutting depth, feed rate and cutting speed. The




13

conclusion reached is that both RSM and RBFN models

reveal that feed rate is the most significant design

variable in determining surface roughness response

compared to others.

Kuttolamadom et al in [5], compares the effects

of a particular combination of a speed and feed on the

surface quality; discovering a different combination of

speed and feed brings into play a hidden effect in terms

of changed machine dynamics caused due to the

difference in surface speeds. This suggests that one

needs to fix the dynamic characteristics of the machine

(i.e., having a fixed vibration amplitude and frequency at

a particular surface speed) before analyzing the rest of

the parameters’ effects on surface quality. Thus,

changing speeds causes a difference in the vibration

dynamics of the machine which remain constant as long

as the surface speed remains constant. However, at a

constant fixed speed, changing feed rates create

differences in surface quality, and these differences can

be attributed predominantly if not completely to

changing feed rates.

Similar investigations were carried out in the

North University Center Baia Mare by LobonŃiu et al. in

[6] and [7]. Their studies were focused on C45 steel

machining, which is a basis for their own research

development.

So, from the research report references and also

from the above studies, I found that all scientific papers

are aimed, one way or another, to investigate the effect

of machining parameters on surface roughness. For this

reason through Figure 1 I want to present the

proportionality of cutting parameters’ influence on

surface roughness.

Fig. 1 Effect of machining parameters on

surface roughness

3 DESIGN OF RESEARCH

In this research, similar to previously analyzed

papers, the attention will focus on aluminum alloys

whose properties are superior to other materials. The

main properties of Aluminum are its light weight,

strength, recyclability, corrosion resistance, durability,

ductility, formability, and conductivity, which make it a

versatile material. Due to this unique combination of

properties, the variety of applications of Aluminum

continues to increase [2]. Because of these properties

aluminum alloys are suitable to process a wide range of

products. The problem with these alloys, however, there

is their difficult machinability due to their hardness and

abrasive nature, which lead to tool wear. Machining

parameters with the greatest influence on alloys’

machinability are the tool type and its coatings, tool

geometry, and cutting regime parameters.

Analyzing the references of research report [1],

I was able to make the graph shown in Figure 2 which

shows the percentage of the most studied aluminum

alloys used in the aircraft industry. As can be seen that

Al6061 covers the majority percentage, followed by

Al7075, because of their superior chemical and

mechanical properties (such as tensile strength and

elongation) compared to other alloys and their

technological manufacturing processes.

Fig. 2. Percentage comparison on the frequency of the

most used aluminum alloys

Also, in the aircraft industry other, less studied

aluminum alloys are used. These alloys are developed

solutions by various specialized companies with the

support of the major aircraft manufacturing companies in

order to improve the manufacturing processes of various

aluminum parts. Therefore, the Al7136 alloy produced

by the Universal Alloy Corporation Company has not yet

been identified in literature in the field of machining.

This is why this paper can be considered one of the first

articles that demonstrates the results of experiments on

this material.

4 EXPERIMENTAL PROCEDURES

1.1 Work Material

The aluminum alloy chosen for the experiment

is an extruded block of Al 7136-T76511 (Al7349 alloy's

equivalent) which comprises 10 rectangular specimens

of 100 mm × 35 mm and 30 mm. This alloy is used in

aerospace industries because of its high strength to

weight ratio and high wear resistance and low thermal

expansion. The chemical composition of specimens is

presented in Table 1.

Table 1. Al7136 chemical composition

Element Min Max

Silicon - 0,12

Iron - 0,15

Copper 1,9 2,5

Manganese - 0,05




14

Magnesium 1,8 2,5

Chromium - 0,05

Zinc 8,4 9,4

Titanium - 0,10

Zirconium 0,10 0,20

Other Elements, each - 0,05

Other Elements, total - 0,15

Aluminum Remainder

The workpiece material is mounted onto the

machine table to provide maximum rigidity. The

workpiece material is parallel to the machine table and

perpendicular to the machine’s spindle head, as the

figure 3 shows.

Fig. 3. Experimental Work on CNC

Vertical Milling Machine

1.2 Equipment and cutting tools used

The experiment was performed by using 16 mm

End milling cutter milling with 50% (8 mm) tool

engagement - SECO R217.69-1616.0-09-2AN, holding

two indexable cutting inserts with ISO coding

XOEX090308FR-E05, H15. The machine used for the

milling tests is a HAAS VF2 CNC. Copious amounts of

coolant were provided at the cutting zone throughout the

experiment.

The end milling was carried out for 10 different

work pieces. Since the inserts were checked for wear

after each run, and no wear was noticeable throughout

the duration of the experiment, the inserts were retained

for the whole experiment. Figure 4 shows the milled

7136 aluminum block with six slot cuts visible on the top

face.

Fig. 4. Milled block with 6 slot cuts visible

For each sample, the process parameters and

their different values are selected based on past research

and on the tool manufacturer indications. Since the

purpose of the experiment is the evaluation of the feed

rate effect on the surface roughness, the selected cutting

speed and cutting depth were held constant. The process

parameters values are shown in table 2.

Table 2. Process parameter values

Cutting speed

[m/min]

Feed per tooth

[mm/tooth]

Cutting depth

[mm]

710

0,020

4

0,033

0,045

0,058

0,070

0,080

0,090

0,100

0,110

0,130

The experiments aim is to improve or reduce

the machining time and get a better surface roughness.

This purpose is established considering the limiting

conditions such as: the CNC’s maximum speed of

13,000 RPM’s, the cutting tool’s diameter, the type of

cutting inserts used in aluminum machining, and the

manufacturer indication on the feed rate variation for

these inserts types.

Feed per tooth has been chosen as a variable

process parameter (assigned values as specified by the

supplier), for the following reasons:

• By the literature analysis I found that this

parameter has the greatest influence on surface quality;

• The Figure 1 show the big influence in surface

quality of feed rate 37%, cutting speed 35% and cutting

depth 28%. All these influences percentage where

identify by experiment or statistical measurement.

• Due to the fact that the feed per tooth variation

can lead to processing time reduction, which is

reinforced by the results in Table 3.

Table 3. Machining time related to each variation of

feed per tooth

Sample Feed per tooth

[mm/tooth]

Machining

time [sec]

1 0,020 124

2 0,033 76

3 0,045 55

4 0,058 43

5 0,070 35

6 0,080 31

7 0,090 27

8 0,100 25

9 0,110 22

10 0,130 19

The surface roughness (response) was measured

by using a portable surface roughness tester (Surftest SJ-

210) as shown in Figure 5. The covered distance by the

measuring device sensor is 5 mm.




15

Fig. 5. Measurement of Surface Roughness Using

Surface Roughness Tester Surftest SJ-210

On each sample, three random measurements

were performed on each passage (Fig. 6).

Fig. 6. The areas representation in which measurements

were made

Table 4. Experimental Plan with Results of Surface

Roughness for 7136 Al alloy

Sample

Feed per

tooth

[mm/tooth]

Climb milling

Surface roughness Ra [µm]

A1 A2 A3

Arithmetic

mean

value A

1 0,020 0,171 0,147 0,197 0,171

2 0,033 0,188 0,18 0,208 0,192

3 0,045 0,222 0,21 0,285 0,239

4 0,058 0,25 0,234 0,264 0,249

5 0,070 0,262 0,258 0,279 0,266

6 0,080 0,319 0,305 0,301 0,308

7 0,090 0,34 0,324 0,361 0,341

8 0,100 0,338 0,349 0,35 0,345

9 0,110 0,349 0,37 0,36 0,359

10 0,13 0,422 0,347 0,351 0,373

Sample

Feed per

tooth

[mm/tooth]

Conventional milling

Surface roughness Ra [µm]

B1 B2 B3

Arithmetic

mean

value B

1 0,020 0,159 0,181 0,146 0,162

2 0,033 0,158 0,18 0,183 0,173

3 0,045 0,22 0,13 0,183 0,177

4 0,058 0,213 0,226 0,178 0,205

5 0,070 0,243 0,235 0,255 0,244

6 0,080 0,288 0,306 0,283 0,292

7 0,090 0,336 0,283 0,304 0,307

8 0,100 0,328 0,323 0,324 0,325

9 0,110 0,335 0,328 0,316 0,326

10 0,13 0,318 0,382 0,351 0,350

For a better understanding of resulting

roughness values from different parameter combinations

in relation to the variable parameter, the average method

was used. Three reading were taken for each

measurement and the average of those three

measurements were considered as the final value (table

4).

5 RESULTS AND DISCUSSION

Surface roughness plays an important role in

many situations and is a decisive factor in the evaluation

of processing accuracy. To achieve the desired quality,

cutting parameters must be controlled because of their

significant influence on surface roughness.

In table 4, the values of the surface roughness of

machined 7136 alloy with varying feed rates values are

presented.

Note that these roughness value sets (A1, A2

and A3) are comparable to each other.

In general, the measurement sets A1 and A3

performed near the samples extremities have a higher

surface roughness compared to the middle sets A2. This

is due to the vibration generated by the tool entering or

exiting the workpiece, which damps quickly with

engagement providing a much smoother surface profile

at the middle section when the cutting dynamics have

stabilized.

Therefore, Figure 6 shows the graphical

representations of the measured roughness values in

climb milling compared to those measured in

conventional milling. Note that the surface roughness

values are plotted in the arithmetic mean value

(Ra),which was in the unit µm from table 3.

So, in both cases (climb milling and

conventional milling), the increase of the measured

surface roughness values from 0.171 to 0.373 µm can be

seen, and respectively, from 0.162 to 0.350 µm. This is

due to the increase in the feed per tooth of 0.02 to 0.13

mm/tooth, which also leads to increasing temperature in

the cutting zone.

Fig. 6. Surface roughness variation on the climb milling

vs. conventional milling

Regarding the graphical evolution of the surface

roughness, Figure 6 also shows that the surface




16

roughness is better on climb milling then on

conventional milling.

In order to more clearly highlight the surface

roughness evolution, in Table 5 I performed a

comparative presentation of the machined surface

topography resulting at different feed rate values.

Microscopic analysis, which involves highlighting the

real distance between two successive tool positions, the

visual representation of the surface texture was carried

out using optical microscopy LEICA DM25M and image

magnification 50X.

Table 5. Surface topography with different

feed per tooth values

Feed per

tooth

[mm/tooth]

Climb milling Conventional milling

Arithmetic

mean

value

Ra[µm]

The

Surface

topography

after one

passage

Arithmetic

mean

value

Ra[µm]

The

Surface

topography

after one

passage

0,020 0,171

0,162

0,033 0,192

0,173

0,045 0,239

0,177

0,058 0,249

0,205

0,070 0,266

0,244

0,080 0,308

0,292

0,090 0,341

0,307

0,100 0,345

0,325

0,110 0,359

0,326

0,130 0,373 0,350

6 CONCLUSIONS

This research paper was done by conducting an

experiment that involves keeping the cutting speed and

cutting depth at constant values, and assigning 10

variable values of feed rate - respecting the range of the

manufacturer's specifications. The end milling of 10

blocks of 7136 aluminum alloy was performed during

the experiment. The paper’s aim was to reduce

machining time and get a better surface roughness. So

based on the conducted research, the following

conclusions resulted:

1. 7136 aluminum alloy used in the aircraft

industry has not been identified in the literature;

2. As the researchers have also shown in their

literature, feed rate has a significant influence on the

surface roughness and this paper is a starting point for

future research, through the results obtained from:

• The information in table 3 showing how to

minimize the cycle time, thus improving productivity

particularly by increasing cutting feeds;

• Figure 6 data processing showing which milling

direction is better in order to obtain the best surface

roughness according to the manufacturer indication on

the feed rate variation; hence the percentage of 37% is

held by conventional milling versus climb milling;

3. In table 5 the visual representation of machined

surface texture supports the findings mentioned above,

and also confirms existing theory.

4. Therefore, the final conclusion is that the

surface quality of the machined surface is improved with

a reduction in the feed rate.

7 FUTURE RESEARCHES

New areas will be studied in future research on

the machining of Al7136 alloy in order to supplement or

improve the industrial processing. Some future

directions of research are mentioned below:

• Investigation of the effect of different tool

geometries on cutting forces of 7136 alloy in milling.

• Investigation of the effect of the coolant on

surface roughness of Al 7136.

• Investigation of the influence of machining

parameters on tool wear in Al 7136 milling.

• Investigation of the effect of tool types with or

without coating on Al7136 aluminum alloy in end

milling.

• Analysis of chip morphology on 7136 alloy in

machining.

• The development of mathematical models for

surface roughness optimization using statistical methods.

REFERENCES

[1] BonŃiu Pop, A.,B., (2011). Proiectarea cercetării şi

identificarea soluŃiilor metodice de proiectare,

Raport de cercetare ştiinŃifică,

[2] Ghan, H. R. and Ambekar, S.D., (2014).

Optimization of cutting parameter for Surface

Roughness, Material Removal rate and Machining

Time of Aluminium LM-26 Alloy. International

Journal of Engineering Science and Innovative

Technology (IJESIT), Vol. 3, Issue 2. [3] Gulhane, U. D., Bhagwat,M.P., Chavan, M.S.,

Dhatkar, S.A. and Mayekar, S.U., (2013).

Investigating the effect of machining parameters on

surface roughness of 6061 aluminium alloy in end

milling. International Journal of Mechanical

Engineering And Technology, Vo. 4, Issue 2, pp.

134-140.

[4] Kadirgama, K., Noor, M.M., Zuki, N.M, Rahman,

M.M., Rejab, M.R.M., Daud, R. and Abou-El-

Hossein, K. A., (2008). Optimization of Surface

Roughness in End Milling on Mould Aluminium

Alloys (AA6061-T6) Using Response Surface

Method and Radian Basis Function Network.




17

Jordan Journal of Mechanical and Industrial

Engineering, Vol. 2, No. 4.

[5] Kuttolamadom, M. A., Hamzehlouia, S., and Mears,

L., (2010). Effect of machining feed on surface

roughness in cutting 6061 aluminum. SAE. Int. J.

Mater. Manuf, 3, p. 108-119.

[6] Lobontiu, M, Hagan, V., Pasca, I., (2011).

Experimental research about evolution of surface

roughness and time for different value of radial

cutting depth in ball end milling of C45 material,

Proceedings of the 15th International Conference

Modern Technologies, Quality and Inovation,

ModTech 2011, Link: http://www.modtech.ro,

ISSN 2069-6736, pag. 569-573.

[7] LobonŃiu Mircea, Paşca Ioan, (2010). Influence of

tool axis inclination angle on the surface roughness

in ball end milling of olc 45 (c45) material,

Proceedings in Manufacturing Systems, No. 1, Vol.

5. Proceedings in Manufacturing Systems , No. 1,

Vol. 5, Ed. Academiei Romane, pag. 39-44.

[8] Tammineni, L. and Yedula, H.P.R., (2014).

Investigation of influence of milling parameters on

surface roughness and flatness. International

Journal of Advances in Engineering & Technology.

[9] Vakondios, D., Kyratsis, P., Yaldiz, S., and

Antoniadis, A., (2012). Influence of milling strategy

on the surface roughness in ball end milling of the

aluminum alloy Al7075-T6. Measurement, 45(6),

1480-1488.

Authors’ addresses

1BonŃiu Pop, Alina Bianca, Phd. Student, Technical

University Cluj Napoca, North University Center Baia

Mare, V. Babeş 62/A, phone +40745-540.608,

[email protected]

Contact person *1

BonŃiu Pop, Alina Bianca, Phd. Student, Technical

University Cluj Napoca, North University Center Baia

Mare, V. Babeş 62/A, phone +40745-540.608,

[email protected]

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