UNIVERSITI TEKNIKAL MALAYSIA MELAKA
SURFACE INTEGRITY ANALYSIS IN CNC MILLING OF
6061-T6 ALUMINUM ALLOY
This report submitted in accordance with requirement of the Universiti Teknikal
Malaysia Melaka (UTeM) for the Bachelor Degree of Manufacturing Engineering
(Manufacturing Process) with Honours.
by
TAN KING HWANG
FACULTY OF MANUFACTURING ENGINEERING
2010
i
ABSTRACT
This study presents the surface integrity analysis and optimization of machining
parameters in 3-axis CNC milling of 6061-T6 aluminum alloy. Aluminum alloy is
widely used in industry such as automation, aerospace and others industry. CNC
milling was selected due to the versatile function. The goal of this research is to
determine the influence of surface roughness and microhardness upon CNC milling
due to the cutting speed, feed rate, and depth of cut. The response surface
methodology (RSM) was used in this study to design and analysis the experiment.
There are 20 trials were conducted by using 3-axis CNC milling machine and the
high speed steel (HSS) end mill with 4 flutes was used in the experiment. The
surface roughness was checked by using portable surface roughness tester, while, the
microhardness were checked by micro DM2D Digital Micro Hardness tester. The
result was analyzed by using the RSM in the Design Expert Software. The
mathematical modeling was established after analysis. The significant parameters
suggested are cutting speed and feed rate while depth of cut is not a significant factor.
For the optimization section, the best predicted setting is cutting speed of 89.99
m/min, feed rate of 191mm/min and depth of cut of 0.57mm in order to archive good
surface finish. The average deviation percentage value is 16.59%. In this experiment,
the microhardness did not have significant changes except for certain trial sample.
ii
ABSTRAK
Kajian ini adalah mengenai analisa integriti permukaan dan mengoptimiskan
parameter mesin pada kelajuan mesin mengisar bagi aluminum aloi 6061-T6.
Objektif kajian ini adalah untuk mengetahui kesan pembolehuabah mesin mengisar
dari segi kelajuan potong, kadar suapan dan kedalaman pemotongan ke atas ‘surface
roughness’ and ‘microhardness’. Kaedah ‘Response Surface Methodology’ (RSM)
telah digunakan untuk menganalisis keputusan. Terdapat 20 kali percubaan yang
dijalankan dengan menggunakan mesin mengisar 3-axis dan mata pemotong berjenis
High Speed Steel (HSS). ‘surface roughness’ telah dinilai dengan menggunakan
‘portable surface roughness tester’, Selain itu, ‘microhardness’ telah dinilai dengan
menggunakan ‘micro DM2D Digital Micro Hardness tester’. Keputusan telah
dianalisis dengan menggunakan kaedah RSM pada perisian ‘Design Expert’. Model
matematik telah diterbitkan dan eksperimen telah dijalankan sakali lagi untuk
mengesahkan model matematik. Dalam seksen optimize, parameter yang diberi
adalah kelajauan potong dengan 89.99 m/min, kadar suapan 191 mm/min dan
kedalaman pemotongan 0.57mm untuk memcapai permukaan yang halus. Bagi nilai
‘average deviation percentage’ adalah memcapai sebanyak 16.59%. Dalam kajian
ini, ‘microhardness’ tiada mempunyai keputusan yang ketara kecuali situasi lain.
Keputusan yang tidak ketara adalah disebabkan oleh menggunakan pendingin masa
menjalankan mesin.
iii
DEDICATION
To my dearest family and friends, for their love, help, and supports.
iv
ACKNOWLEDGEMENT
I would like to take this opportunity to express my gratitude towards the following
groups of people which not only given me continuous support and guidance
throughout the entire course of this project paper. First and foremost, I would like to
extend my deepest appreciation and thanks towards my supervisor, Miss Liew Pay
Jun, who not only guided me but also provided me the knowledge and means to
completing this research.
This report would not have been possible without the help of the staff from ADTEC
and UTHM who helped me in conducting the experiment. My sincere thanks also go
to the UTeM faculty of manufacturing’s technician whom help me in collecting data.
Last but not least, I would like to thank my family and friends that provided me
never-ending support, care and assistance in completing my project.
v
TABLE OF CONTENT
Abstract i
Abstrak ii
Dedication iii
Acknowledgement iv
Table of Content v
List of Tables ix
List of Figures x
List Abbreviations xii
1. INTRODUCTION 1
1.1 Introduction 2
1.2 Background of Problem 2
1.3 Statement of Problem 2
1.4 Objective 3
1.5 Scope 3
1.6 Importance of Study 3
1.7 Expected Result 4
2. LITERATURE REVIEW 5
2.1 Machining Center 5
2.2 Milling Machine Operation 6
2.2.1 End Milling 6
2.3 Milling Parameter 7
2.3.1 Cutting Speed 8
2.3.2 Feed Rate 8
2.3.3 Depth of Cut 9
2.4 6061-T6 Aluminium Alloy 9
2.5 Cutting Tool 10
2.6 Response Variable 11
2.6.1 Surface Roughness 11
vi
2.6.2 Microhardness 14
2.7 Design of Experiment 15
2.7.1 Response Surface Methodology 15
2.7.1.1 Central Composite Design (CCD) 16
2.8 Finding from Past Researches 18
2.9 Summary 22
3. METHODOLOGY 23
3.1 Define the Objective of the Experiment 23
3.2 Determine the Input Parameters at Low Level and High Level 23
3.3 Design of Experiment Matrix 24
3.4 Identify the Appropriate Response Variable 24
3.5 Preparation of the Experiment 25
3.5.1 Workpiece Preparation 25
3.5.2 Cutting Tool 27
3.5.3 HAAS VF Series Vertical Machining Centre 27
3.5.4 Testing of Surface Roughness 28
3.5.5 Testing of microhardness (Vicker test) 29
3.5.6 Analysis the Results 32
3.5.7 Develop Mathematical Model of Response Surface with the Best Fittings 32
3.5.8 Validation of Experimental Parameters 33
3.6 Conclusion and Recommendation 33
3.7 Flow Chart of Study 34
4. RESULT AND DISCUSSION 35
4.1 Result 35
4.2 Analysis 36
4.2.1 Transformation 36
4.2.2 Fit Summary 37
4.2.2.1 Sequential Model Sum of Square 37
4.2.2.2 Lack of Fits Test 38
4.2.2.3 Model Summary Statistic 38
4.2.3 Model 39
vii
4.2.4 ANOVA 39
4.2.4.1 Summarize value of Analysis of variance 40
4.2.5 Diagnostic 41
4.2.5.1 Normal % Probability versus Internally Studentized Residuals 41
4.2.5.2 Plot of residuals vs. predicted surface roughness values 42
4.2.6 Model Graphs 43
4.2.6.1 One Factor graph of cutting speed (A) versus Surface Roughness 43
4.2.6.2 One Factor graph of feed rate (B) versus Surface Roughness 45
4.2.6.3 One Factor graph of depth of cut (C) versus Surface Roughness 46
4.2.6.4 Perturbation graphs of Factor A, B and C 47
4.2.7 3D modelling graph 48
4.2.7.1 3D modeling of cutting speed (A) and feed rate (B) to respond of surface
roughness 48
4.2.7.2 3D modeling of cutting speed (A) and depth of cut (C) to respond of surface
roughness 50
4.2.7.3 3D modeling of feed rate (B) and depth of cut (C) to respond of surface
roughness 52
4.2.7.3 A cube box that show the interaction between cutting speed (A), feed rate (B)
and depth of cut(C) 54
4.3 Optimization 55
4.3.1 Numerical 55
4.3.2 Ramp Function Graph 56
4.4 Confirmation Run 57
4.4.1 Average Deviation Percentage Value 57
4.5 Microhardness 59
4.5.1 Sample std run 10 (highest cutting speed) 59
4.5.2 Sample std run 12 (highest feed rate) 60
4.5.3 Sample std run 14 (highest depth of cut) 61
4.5.4 Other Samples 62
viii
5. CONCLUSION AND RECOMMENDATIONS 63
5.1 Conclusion 63
5.2 Recommendations 64
5.2.1 Recommendations of result improvement 64
5.2.2 Recommendations of Further Study 64
REFERENCES 65
APPENDICES
A Gantt chart for PSM 1
B Gantt chart for PSM 2
C Result for microhardness
ix
LIST OF TABLES
2.1 Summarized of journal 18
3.1 Variable Factors Levels 23
3.2 Design Matrix Generated by Design Expert 7.1.6 software 24
3.3 Mechanical Properties of 6061-T6 Aluminium Alloy 26
3.4 Chemical Composition of 6061-T6 Aluminium Alloy 26
3.5 Mechanical Properties of High Speed Steel (HSS) 27
4.1 Surface Roughness Value of Variety Setting 35
4.2 Sequential Model Sum of Square [Type 1] 37
4.3 Lack of Fits Test 38
4.4 Model Summary Statistic 38
4.5 Analysis Of Variance Table [Partial sum of squares-Type III] 39
4.6 Summarize Value of Analysis of variance table 40
4.7 Solution Value Suggested By Design Expert Software 55
4.8 Surface Roughness Value for Random Trials 57
4.9 Values of Surface Roughness Obtained From Confirmation Trials & the
Deviation Percentage with the Predicted Values 58
4.10 Trial 10 parameter 59
4.11 Trial 12 parameter 60
4.12 Trial 14 parameter 61
x
LIST OF FIGURES
2.1 End Milling 6
2.2 Movement of the VCM Machine 7
2.3 Surface Roughness Profile 11
2.4(a) Parameters That Affect Surface Roughness 12
2.4(b) Parameters That Affect Surface Roughness after Screening 13
2.5 Points in the Factorial Portion 16
2.6 Points in Axial Points 16
2.7 Factorial and Axial Portions with Centre Point 17
3.1 Flow Chart of Workpiece Preparation 25
3.2 HSS End Mill with 4 Flutes 27
3.3 Okuma MX-45VA-R Vertical Machining Centre 28
3.4 Portable Surface Roughness Tester SJ-301 28
3.5(a) DM2D Digital Micro Hardness Tester 29
3.5(b) Diamond Cutter Machine 29
3.5(c) Experiment Sample 30
3.5(d) Mounting Press Machine 30
3.5(e) SiC Sand Paper 31
3.5(f) Grinding Machine 31
3.5(g) Polishing Machine 31
3.6 The Flow Chart of Experiment Work 32
3.7 Flow Chart of Study 34
4.1 Graph Box-Cox Plot for Power Transform 36
4.2 Normal Probability Plot of Residuals for Surface Roughness Data 41
4.3 Plot of Residuals vs Predicted Surface Roughness Values 42
4.4 One Factor Graph of Cutting Speed (a) versus Surface Roughness 43
4.5 One Factor Graph of Feed Rate (b) versus Surface Roughness 45
4.6 One Factor Graph of Depth of Cut (c) versus Surface Roughness 46
4.7 Perturbation Graphs of Factor A, B and C 47
xi
4.8(a) 3D Modeling Of Cutting Speed (A) and Feed Rate (B) To Respond 48
of Surface Roughness
4.8(b) Contour Graph of Cutting Speed (A) And Feed Rate (B) To Respond 48
of Surface Roughness
4.9(a) 3D Modeling of Cutting Speed (A) and Depth of Cut (C) To Respond 50
of Surface Roughness
4.9(b) Contour Graph of Cutting Speed (A) and Depth of Cut (C) To Respond 50
of Surface Roughness
4.10(a) 3D Modeling Of Feed Rate (B) And Depth of Cut (C) To Respond 52
of Surface Roughness
4.10(b) Contour Graph of Feed Rate (B) and Depth of Cut (C) To Respond 52
of Surface Roughness
4.11 A Cube Box That Show the Interaction between Cutting Speed (A), 54
Feed Rate (B) And Depth Of Cut(C).
4.12 Ramp Function Graph 56
4.13(a) Graph HV Hardness versus Distance for Sample 10 59
4.13(b) Graph HV Hardness versus Distance for Sample 12 60
4.13(c) Graph HV Hardness versus Distance for Sample 14 61
xii
LIST OF ABBREVIATIONS
CNC - Computer Numerical Control
HSS - High Speed Steel
rpm - Revolution per minute
DOE - Design of Experiment
RSM - Response Surface Methodology
ANOVA - Analysis of variance
1
CHAPTER 1
INTRODUCTION
This chapter gives a brief overview of 3-axis CNC milling technology. Besides, this
chapter includes the objective, scope, problem statement and importance of study.
1.1 Introduction
Kauppinen (2004) stated that CNC milling has been widely recognised as one of the
key processes in fabricating aluminium parts in variety of manufacturing industry
included aerospace and automotive sectors where to produce high precession and
accuracy parts. Some major benefits of the CNC milling compared to conventional
milling are reported as high material removal rate, reduction in lead time, low cutting
force, and dissipation of heat from the cutting zone is transferred mainly into chips,
resulting in high accuracy and better surface finish.
Furthermore, Kalpajian (2004) classified that surface roughness is using to determine
the surface finish. Surface roughness influence several functional attributes of parts
such as contact causing surface friction, wearing, light reflection, heat transmission
or resisting fatigue. Besides, microhardness influence scratch and wear resistance.
Therefore, selecting the appropriate machine parameter to achieve desired surface
finish is very important.
Kauppinen (2004) stated that the machinability of aluminium alloys is relatively high.
Milling aluminium materials with conventional cutting parameters is easy. Cutting
forces are low and tool wear relatively small. Tool wear rates of the cutting tools do
not normally play a significant role in the machining of aluminium alloys. The 6061-
2
T6 aluminium alloys have been choosing in this study because it was widely and
successfully used in aeronautical, dies and mould industry.
1.2 Background of Problem
The elevated cutting speed of the CNC milling will yield unexpected mechanical
force and thermal cycle on the material. Furthermore, the improper or inadequate
selection of the machining parameters will cause the surface defects such as cracks,
creep, and plastic deformation to cause an overall deterioration of the component’s
mechanical properties. An undesired surface finish will decrease the fatigue life or
durability and cause an unwanted failure happen. Besides, scratches or scribe marks
may appear on the surface of structures in service due to unpredicted damage,
repairing actions or application of large decals. Zhao et al (2009) reported that the
preliminary stage is tiny but may increase the potential risk of fatigue failure for the
structures of airplanes or other aerospace vehicles under the variable service loads.
Furthermore, traditional ‘trial and error’ method are time consuming and inaccurate.
Therefore, in this study, an analysis and optimization of the surface finish was
carried out.
1.3 Statement of Problem
� Improper or inadequate selection of the machining parameters will cause the
surface defect such as crack, and plastic deformation to cause an overall
deterioration of the component’s mechanical properties.
� Traditional ‘trial and error’ method are time consuming and inaccurate.
3
1.4 Objective
The objectives of this paper are:
• To analyze the effect of CNC milling parameters such as cutting speed, depth
of cut, and feed rate to the surface roughness and microhardness of 6061-T6
Aluminium Alloy.
• To determine the best setting for the machining to achieve the best result of
surface roughness by using Response Surface methodology (RSM).
1.5 Scope
This study investigates the effect of cutting speed, feed rate, and depth of cut on the
surface finish of the material upon the high speed end milling. The material was used
in this study is 6061-T6 aluminium alloy. On the other hand, the cutting tool that
used in this study is high speed steel (HSS). Furthermore, the response surface
methodology (RSM) was applied to generate the experiment matrix. Finally,
mathematical model was developed to represent the study and validation was
conducted to determine the consistency of the mathematical model. Others responses
such as, cutter geometry, and tool wear were not discussed in this study.
1.6 Importance of Study
CNC milling has becomes a cost-effective manufacturing process to produce parts
with high precision and good surface quality. By applying the RSM method, the
correlation of machining variables and responses (surface roughness and
microhardness) could be obtained easily. This will help the industry to save time and
cost compared to the previous “trial and error” method. Besides, by identifying the
optimum parameters setting could help the industry to reduce the product failure
which caused by surface finish problems.
4
1.7 Expected Result
The main factors that influence the surface finish of material are cutting speed, feed
rate, and depth of cut. Different value of parameters will result different surface
finish. By applying RSM method, the most influential parameter and relation
between the parameter and response can be analysed. The mathematical modelling
will be established and the optimal surface finish will be obtained at the end of the
study.
5
CHAPTER 2
LITERATURE REVIEW
This chapter describes the theory of milling process and the parameters by referring
from the journal. Besides, cutting tool, workpiece, response variable and summary of
journal were explained in this chapter.
2.1 Machining Center
Kalpajian (2004) reported that a machining centers is an advanced, computer
controlled machine tools that is capable of performing a variety of machining
operations on different surfaces and different orientations of a workpiece without
having to remove it from its workholding device or fixture. The workpiece is
generally stationary, and the cutting tools rotate as they do in milling, drilling,
honing, tapping, and similar operations. Whereas in transfer lines or in typical shops
and factories the workpiece is brought to the machine, note that in machining centers,
it is the machining operation that is brought to the workpiece. CNC machine allow
more operation to be done on a part in one setup instead of moving from machine to
machine for various operations. These machines greatly increase productivity
because the time formerly used to move a part from machine to machine is
eliminated.
.
6
2.2 Milling Machining Operation
2.2.1 End Milling
Kalpajian (2004) classified that the cutter called end mill has either straight shank or
a tapered shank and is mounted into the spindle of the milling machine. End mill can
produce variety type of surfaces at any depth such as curved, stepped and pocketed.
The cutter removes material on both its end and its cylindrical cutting edges as
shown at Figure 2.1. One of the more common applications is high speed milling
using an end mill, which observes the same general provisions regarding the stiffness
of machines, workholding devices, etc. Consequently, end milling process was
selected to carry out in this study.
Figure 2.1: End milling.
7
Figure 2.2: Movement of the VCM machine.
2.3 Milling Parameter
There are several type of parameters exist in milling machine or milling process,
such as cutting force, feed rate, depth of cut, cutting speed, spindle speed, cutting
temperature and etc. Those parameters will affect the response variable depend on
the input.
From the literature review, Rao and Shin (2001) revealed that the parameters such as
feed rate, cutting speed and depth of cut will affect the surface finish. Besides, the
increasing depth of cut is shown to slightly deteriorate surface roughness.
Furthermore, Sun and Gou (2009) classified that the cutting speed, feed rate, and
depth of cut affected surface roughness and residual stress. Moreover, Suresh Kumar
Reddy et al (2008) shown that the most influential factors affecting the surface finish
consider as cutting speed, feed, and depth of cut. Furthermore, Benardos and
Vosnaikos (2003) reported that the cutting speed, feed rate and depth of cut are
parameters that mostly influence the Ra value of surface quality in machining,
particularly in the milling machining process. And lastly, Zhang et al (2006)
mentioned that the cutting speed was a significant factor affecting surface roughness.
In the literature, the effect of the different parameters on the surface integrity was
researched. In this study, cutting speed, feed rate, and depth of cut as machining
conditions will be selected.
8
2.3.1 Cutting Speed
Seames (2002) stated that the cutting speed is the edge or circumferential speed of a
tool. In a machining center or milling machine application, the cutting refers to the
edge speed of the rotating cutter. Proper cutting speed varies from material to
material. Basically, the softer the materials, the higher the cutting speed will be
choosing.
���������� � ������ � ��� � ��
2.3.2 Feed Rate
Seames (2002) reported that feed rate is the velocity at which the cutting tool is feed
into the workpiece. Feed rate are critical to the effectiveness of a job. Too heavy a
feed rate will resulting a premature dulling and burning of tools. While, feed rate
with too light will result in tool chipping. This chipping will rapidly lead to cool
burning and breakage. Moreover, Kalpajian (2004) classified that it is often express
in unit inch per minutes (ipm) or millimetres per minutes (mm/min) with
consideration of how many teeth or flutes.
Basic formula for feed rate:
� � � � � � ��
Where:
F=the milling feed rate expressed in mm per minute
R=the chip load per tooth
T=the number of teeth on the cutter
rpm=the spindle speed in revolution per minute
(2)
(1)
