Uses taguchi method to analyse the WEDM parameters.The orthogonal array,signal to noise ratio,ANOVA are also employed on this analysis

1. Optimization of Wire Electric
Discharge Machining Parameters Of
Al 6061
Group No. 2
Team Guide Team Members
Asst. Prof. Bibin K Tharian Basil Raju (14010030)
Mechanical Dept. Basil Skaria(14010032)
MBITS Eldhose Kuriakose (14010050)
Geo Mathew(14010055)

2. OUTLINE OF THE PRESENTATION
• Introduction
• Working Principle
• Literature Survey
• Findings from literature survey
• Objectives of present research
• Methodology
1

3. INTRODUCTION
• Importance of machining
• Types of machining
• Conventional & non conventional machining
• Comparison
• WEDM
• Importance of WEDM
• Applications
2

4. WORKING PRINCIPLE
Fig 1 : Schematic representation of WEDM.3

5. Fig 2: Electronica Ultra cut S1 WEDM
4

6. WORKING PRINCIPLE
• Spark erosion technique
• Dielectric breakdown
• Plasma channel formation
• Generation of pressure shock waves
• Material removal
5

7. LITERATURE REVIEW ON WIRE EDM
SI NO AUTHOR YEAR CONTRIBUTION
1 Pragya shandilya ,
P K Jain,
N K Jain
2012 • Analysis & optimization
• Resources: pulse on time, pulse off time,
Wire feed rate , Servo voltage
2 C D Shah, J R Mevada ,
B C Khatri
2013 • Optimization of process parameters of
WEDM by response surface methodolgy
6

8. LITERATURE REVIEW ON WIRE EDM
SI
NO.
Author Year Contribution
3 Kasinath Das Mohaptra,
S K Sahio
2014 • Parametric optimization of WEDM
process for gear cutting
• Response: MRR, Single pitch error
4 Harsimran Singh,
Harmesh kumar
2015 • Review of process parameters of WEDM
by response surface methodology
7

9. LITERATURE REVIEW ON AI6061
SI NO Author Year Contribution
1 Sharag Nair , Nehal
joshi
2015 • Preparation of AI 6061 matal matrix
composite
2 A.Muniappan,
C.Thiagarajan
S Somasundaram
2017 • Parametric optimisation of kerf width &
Ra in WEDM of AI6061 composite
8

10. LITERATURE REVIEW ON OPTIMIZATION TECHNIQUE
SI NO Author Year Contribution
1 K B Rai & P .R Dewan 2014 • Parametric optimization of WEDM using
GRA with Taguchi method
2 Siva prasad,
Arikatla.K,
Tamil mannan,
Arkanti krishniah
2016 • Factors : pulse on time, Pulse off time,
Servo voltage, Wire tension
• Response : MRR, Ra
9

11. FINDINGS FROM LITERATURE SURVEY
• WEDM is mainly employed for difficult to machine materials.
• Only few work has been done in the parameter optimization of
Al6061 aluminium alloy.
10

12. OBJECTIVES OF PRESENT RESEARCH
• To find optimal machining performance for surface roughness and
material removal rate.
• To evaluate the quality of surface roughness produced.
• To generate a mathematical model for surface roughness & MRR.
• Find the significance of parameters using ANOVA
• Parameter optimization using GRA.
11

13. METHODOLOGY
12

14. MATERIAL SELECTION
• Material : Aluminium 6061
• Good mechanical properties and good weldability.
• Application: aircraft & aerospace components,marine fittings, bicycle
frames , drive shafts , brake components, valves, couplings
Table 1: Chemical composition of Al6061.
components Al Mg Si Fe Cu Zn Cr Ti Others
Wt%
98.5-
98.56
.8-
1.2
.4-.8 0.7 .15-.4 0.25
0.04-
.35
0.15
0.05-
.15
13

15. SELECTION OF INPUT AND OUTPUT PARAMETERS
WEDM PROCESS
Machining parameter
Pulse ON time
Pulse OFF time
Feed rate
Current
Performance Measure
Surface Roughness
Material Removal Rate
14

16. TAGUCHI METHOD
• Developed by Dr. Genichi Taguchi
• The objective is to make the “IMPROVEMENT OF QUALITY”.
• Taguchi recommends orthogonal array (OA)
• The standard two level and three level arrays are:
•Two level arrays: L4, L8, L12, L16, L32
•Three level arrays: L9, L18, L27
• L9 OA is chosen with 4 parameters
15

17. FACTORS AND LEVELS
Table 2: Factors and levels
SL
NO.
FACTOR UNIT SYMBOLS LEVEL 1 LEVEL 2 LEVEL 3
1
PULSE ON TIME
(T ON)
Micro
Seconds
A 100 110 120
2
PULSE OFF TIME
(T OFF)
Micro
Seconds
B 51 55 59
3 FEED RATE (F) mm/min D 3 6 9
4 CURRENT (I) Ampere C 10 11 12
16

18. DESIGN OF EXPERIMENT
Table 3: DOE
Sl.
No.
Pulse on Pulse off Current Wire feed rate
1 100 51 10 3
2 100 55 11 6
3 100 59 12 9
4 110 51 11 9
5 110 55 12 3
6 110 59 10 6
7 120 51 12 6
8 120 55 10 9
9 120 59 11 3
17

19. EXPERIMENTAL DATA
Table 4: Experimental data
Sl.
No.
Pulse on Pulse off Current
Wire feed
rate
Time for
cutting
Surface
roughnes
s
MRR
1 100 51 10 3 37.27 1.46 0.00295
2 100 55 11 6 9 2.48 0.013
3 100 59 12 9 9.04 2.46 0.0132
4 110 51 11 9 2.42 3.16 0.0537
5 110 55 12 3 2.23 3.68 0.0538
6 110 59 10 6 31.43 1.78 0.00381
7 120 51 12 6 4.13 4.2 0.0363
8 120 55 10 9 39.12 1.9 0.00281
9 120 59 11 3 3.53 3.72 0.0368
18

20. TAGUCHI ANALYSIS
19

21. ANALYSIS FOR SURFACE ROUGHNESS
Fig 3: Mean graph for Ra.
20

22. ANALYSIS FOR SURFACE ROUGHNESS
Fig4: SN ratio graph for Ra
Optimum parameter combination : A 1B3C1D3
21

23. From the main effects plot for S/N ratio, the optimum parameter
combination for surface roughness is,
Pulse ON time= 100µs
Pulse OFF time= 59µs
Feed rate= 9mm/min
Current= 10A
22

24. ANOVA RESULTS IN PIE CHART FOR Ra
26.66%
1.95%
27.32%
4.17%
PERCENTAGE CONTRIBUTION
PULSE ON
PULSE OFF
CURRENT
FEED RATE
23

25. REGRESSION EQUATION FOR Ra
Using Minitab 15.0 software, regression equation has been generated
for surface roughness
Ra= - 10.6 + 0.0570 A - 0.0358 B+ 0.868 C- 0.0748 D
Where,
A= Pulse ON time
B= Pulse OFF time
D= Feed rate
C= Current
24

26. ANALYSIS FOR MATERIAL REMOVAL RATE
Fig 5: Mean graph for MRR.
25

27. ANALYSIS FOR MATERIAL REMOVAL RATE
Fig 6:S/N ratio graph for MRR.
Optimum parameter combination :A2B1C3D126

28. From the main effects plot for S/N ratio, the optimum parameter
combination for Material Removal Rate is,
Pulse ON time= 110µs
Pulse OFF time= 51µs
Feed rate= 3mm/min
Current= 12 A
27

29. ANOVA RESULTS IN PIE CHART FOR MRR
31.24%
7.13%
56%
7.60%
PERCENTAGE CONTRIBUTION
PULSE ON
PULSE OFF
CURRENT
FEED RATE
28

30. REGRESSION EQUATION FOR MRR
Using Minitab 15.0 software, regression equation has been generated for
Material Removal Rate
MRR = - 0.136 + 0.000779 A - 0.00163 B + 0.0156 C - 0.00132 D
Where,
A= Pulse ON time
B= Pulse OFF time
D= Feed rate
C= Current
29

31. GREY RELATIONAL ANALYSIS
30

32. GREY RELATIONAL GRADE AND COEFFICIENT
Table 5: Grey relational coefficient and grade
EXP
NO.
GREY RELATIONAL
COEFFICIENT
GREY RELATIONAL
GRADE
RANK
MRR Ra
1 0.33399 1 0.666972 3
2 0.384569 0.57322 0.478895 8
3 0.385733 0.578059 0.481896 7
4 0.996093 0.446254 0.721174 1
5 1 0.381616 0.690808 2
6 0.337744 0.810651 0.5742 4
7 0.592976 0.333333 0.463155 9
8 0.333333 0.756906 0.54512 5
9 0.599953 0.37741 0.488682 6
31

33. ANALYSIS FOR GRA
Fig7 :Mean graph for gra
32

34. ANALYSIS FOR GRA
Fig8:S/N ratio graph for GRA
• Optimum parameter combination :A2B1C1D133

35. ANOVA RESULTS IN PIE CHART FOR GRA
52.40%
19.28%
4.76% 23.50%
PERCENTAGE CONTRIBUTION
PULSE ON
PULSE OFF
CURRENT
FEED RATE
34

36. REGRESSION EQUATION FOR GRA
Using Minitab 15.0 software, regression equation has been generated for
GRA
GRA = 1.82 - 0.00218 A - 0.0128 B - 0.0251 C - 0.0055 D
= 0.6727
Where,
A= Pulse ON time=110µs
B= Pulse OFF time=51µs
C= Current=10A
D= Feed rate=3mm/min
35

37. SINGLE V/S MULTI OPTIMISATION
Table 6: Single v/s Multi Optimisation
Parameter
Optimized
Combination
Ra(µm)
MRR(
mm3/min)
Ra A1B3C1D3 0.9946 -0.01015
MRR A2B1C3D1 4.0358 0.0498
Ra and MRR A2B1C1D1 2.2998 0.0186
36

38. CONCLUSION
Based on the Taguchi optimization conducted
• Most significant parameter affecting Ra and MRR
separately are current.
• Least significant parameter affecting Ra and MRR
separately are pulse off time
• Most significant parameter affecting Ra and MRR
simultaneously pulse on time.
• Least significant parameter affecting Ra and MRR
simultaneously are current
37

39. REFERENCES
1. A.Muniappana, C.Thiagarajan B and S.Somasundram C
“Parametric Optimization of KERF Width and Surface
Roughness in Wire Electrical Discharge Machining
(WEDM) of Hybrid Aluminium (Al6061/SIC/GRAPHITE)
Composite using Taguchi-Based Gray Relational
Analysis” International Journal of Mechanical &
Mechatronics Engineering IJMME-IJENS Vol:17
No:01,pp.205-208 .
38

40. 2. Adnan Akkurt “The effect of cutting process on surface
microstructure and hardness of pure and Al 6061
aluminium alloy” Engineering Science and Technology, an
International Journal (2014) 1e6,pp.2391-2398
3. Bibin, K.T, Kuriachen, B, Paul J, and Elson P.V, “Surface
Roughness Optimization of Wire Electrical Discharge
Machining on AISI 202 Using ABC Algorithm” Applied
Mechanics and Materials, Vols. 766-767, (2015), pp. 902-
907
39

41. THANK YOU
40

42. APPENDIX
Equations used for GRA,
Smaller the better,
Larger the better,
Deviation sequence,
Grey relational coefficient,
Grey relational grade,
41

43. SEQUENCES AFTER DATA PROCESSING
Table 7 : Sequences after data processing
EXPERIMENT NO. MRR Ra
REFERENCE
SEQUENCE
1.00000 1.0000
1 0.002746 1
2 0.199843 0.627737
3 0.203765 0.635036
4 0.998039 0.379562
5 1 0.189781
6 0.019612 0.883212
7 0.656795 0
8 0 0.83946
9 0.666601 0.175182
42

44. DEVIATION SEQUENCES
Table 8 : Deviation sequences
DEVIATION
SEQUENCE
∆(1) ∆(2)
EXP NO.1 0.997254 0
EXP NO.2 0.800157 0.372263
EXP NO.3 0.796235 0.364964
EXP NO.4 0.001961 0.620438
EXP NO.5 0 0.810219
EXP NO.6 0.980388 0.116788
EXP NO.7 0.343205 1
EXP NO.8 1 0.160589
EXP NO.9 0.333344 0.824818
43

45. ANOVA BASED ON S/N RATIO FOR Ra
Table 9 : ANOVA based on S/N ratio for Ra
Control factors DOF Sum of square Mean squares
Percentage
contribution
Pulse ON
time(A)
2 2.00720 1.0036 26.55%
Pulse OFF
time(B)
2 0.14747 0.07373 1.95%
Current (C) 2 5.08987 2.54493 67.32%
Feed Rate (D) 2 0.31547 0.15773 4.17%
Total 8 7.56
44

46. ANOVA BASED ON S/N RATIO FOR MRR
Table 10 : ANOVA based on s/n ratio for MRR
Control factors DOF Sum of square Mean squares
Percentage
contribution
Pulse ON
time(A)
2 0.0011322 .0005661 31.24%
Pulse OFF
time(B)
2 .0002585 00001292 7.13%
Current (C) 2 0.0019565 0.0009782 56%
Feed Rate (D) 2 0.0002755 0.0001377 7.6%
Total 8
45