Machining Accuracy Based On Taguchi Optimization Technique Biology Essay

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Wire electical discharge machining one of the most popular machine to machining the alloying material such as Titanium alloy. The high degree of obtainable accuaracy in machining make WEDM valuable.

This research is going to machining kerf, thin section and corner cutting on Titanium alloy. The machining parameters setting is pulse on time (TON), pulse off time (TOFF), peak current (IP) and wire speed (WS). The experimental design based on Taguchi method and optimized by using Analysis of Variance (ANOVA).

The results of the experiment shows that TON, TOFF and wire speed of the WEDM are significant on kerf. The TON, TOFF and peak current are the significant factors for thin section cutting. While for corner cutting all factors are influence. Hence, the TON and wire speed mainly should be control to achieve desired accuracy in machining by Wire-EDM.

Keywords: WEDM; Taguchi Method; kerf; thin section cutting; corner cutting

1. Introduction

Accuaracy aspect is important factor to consider in machining part for aerospace and mold/die industries. A non contact machining technique makes wire electrical discharge machining (WEDM) to be suitable for processing high accuracy and good roughness of surface. The machining accuaracy form include straightness, kerf, thin section and corner cutting (McGeough, 1988).

The kerf (k) in WEDM known as a cutting width. It is depend on the wire diameter (dWE) and over cut (s ) which show on below formula:

k = dWE + 2s (a)

According to Tosun and Cogun (2004), using Taguchi experimental design method and ANOVA to find the level of significant parameter affecting minimum kerf and maximum material removal rate (MRR). They found, the highly of effective parameter on both the kerf and MRR is open circuit voltage and pulse duration. The larger TON setting, causes MRR and kerf increases because more bigger crater occur on machining surface (Liao et al., 1997)

Thin section cutting with high accuracy is critical aspect in machining by WEDM. This happen because machining done by thermal electric process. Scott F.M. (2005) a minimum thin section machining depends on electrical spark energy, thermal stress and material removal rate. They found the minimum thickness in WEDM, is more dependent TON rather than pulse duration (TON-TOFF).

Inaccuracy corner cutting depend on reactant forces (Dekeyser and Snoeys, 1989), wire lag phenomena (Puri and Bhattacharyya, 2003), thickness of part, corner radius and number of trim cut (Sanchez, 2007). Hsue et al. (1999) found the MRR in corner cutting is quite different from that in straight path cutting. Little research work has been carried out on WEDM parameters process. Therefore, we believe corner performance also depend on several WEDM parameters such as TON, TOFF, peak current, open voltage, wire tension, wire speed and flushing pressure.

However, selection of optimum machining parameters to obtain higher dimensional accuracy characteristics is become challenging task in WEDM. These because WEDM have large number of process variable and complicated stochastic process mechanism. Due to large number of process variables, a planned set of experiments is conducted according Taguchi's orthogonal array (Taguchi, 1990). Then, indentify the significant factors using ANOVA approach.

The purpose of this research is to optimize machining parameters setting such as pulse on time, pulse off time, peak current and wire speed on kerf, thin section and corner cutting. The optimization is determined based on Taguchi method with orthogonal array L934 and Analysis of Variance (ANOVA).

2. Machining Preparation

The machining was performed on a WEDM machine types SODICK AQ327L with brass electrode wire 0.25mm in diameter. The material preparation divided to three (3) machining based our performances require such as kerf, thin cutting (1mm) and corner cutting with radius 2mm. The results determine using Scanning Electron Microscope (SEM) to capture the images and measure dimension of machining samples.

3. Process of experimental design

Taguchi method use in the research because 1) To reduce number of experiment, 2) To determine the best set of parameters combination and 3) To predict optimum result according optimum parameters setting. While ANOVA use as an optimization analysis to finding the significant factors influence experimental results.

3.1. Selection of the factors

According to the references journal, there are several factors that can affect accuracy of machining which are pulse duration, peak current, open voltage, wire tension, wire speed and flushing pressure. However, this research only focus on most important factors effect on machining accuracy such as pulse on time, pulse off time, peak current and wire speed.

3.2. Selection of the factor levels

There are three level of each factors and set into low, middle and high values. The setting values ranges following result from preliminary test. Each level parameter of the selected factors that suggested to this research is shown in Table 1.

Table 1

The parameter for three levels of selected factors

Factors

Level 1

Level 2

Level 3

Pulse on time, TON (µs)

3

5

7

Pulse off time, TOFF (µs)

10

14

18

Peak current, IP (A)

5

10

15

Wire speed, WS (mm/min)

50

100

150

3.3. Selection of orthogonal array

The L9 is chosen as an orthogonal array because it is suitable for four factors with three levels. That orthogonal array is shown in Table 2.

Table 2

The L9 orthogonal array

No.Trial

Column no. for factors

TON

TOFF

IP

1

1

1

1

2

1

2

2

3

1

3

3

4

2

1

2

5

2

2

3

6

2

3

1

7

3

1

3

8

3

2

1

9

3

3

2

3.4. The combination parameters on orthogonal array L9

The experiment is started by keying all the combination parameters for each factors into WEDM machine as shown in Table 3. There are nine experiments run with different combinations. Then measurements are taken for kerf, thin section and corner cutting shown in Table 4.

Table 3

The combination parameters for each factors on L9 experimental.

No.Trial

Column no. for factors

Pulse on time

TON(µs)

Pulse off time

TOFF(µs)

Peak current

IP (A)

1

3

10

5

2

3

14

10

3

3

18

15

4

5

10

10

5

5

14

15

6

5

18

5

7

7

10

15

8

7

14

5

9

7

18

10

4. Results and discussion

In determination of signal to noise (S/N) ratio, the smaller the better quality characteristic has been selected for kerf. While nominal the better quality characteristics for thin section and corner cutting. The results that calculated for kerf, thin section and corner cutting are summarized in Table 4.

Table 4

Summarize of the experimental result for kerf, thin section 1mm and corner radius 2mm cutting

No.Trial

Column no. for factors

Kerf

(µm)

S/N

(kerf)

Thin

Section (µm)

S/N (Thin section)

Corner cutting (mm)

TON

(µs)

TOFF(µs)

IP

(A)

WS (mm/min)

1

3

10

5

50

297.33

-49.46

958.00

-32.46

1.7514

2

3

14

10

100

296.33

-49.44

967.00

-30.37

1.7919

3

3

18

15

150

301.33

-49.58

973.00

-28.63

1.8319

4

5

10

10

150

303.00

-49.63

975.00

-27.96

1.7554

5

5

14

15

50

304.00

-49.66

964.00

-31.13

1.8369

6

5

18

5

100

302.00

-49.60

958.00

-32.46

1.7174

7

7

10

15

100

298.67

-49.50

961.00

-31.82

1.7139

8

7

14

5

150

302.33

-49.61

960.00

-32.04

1.6864

9

7

18

10

50

303.67

-49.65

960.00

-32.04

1.7789

The data taken in Table 4 use to determine average S/N ratio for kerf, thin section and corner cutting. The examples of calculations for each response are shown below and the result summarized as shown in Table 5-7 respectively.

Kerf

For factor duration of pulse on time,

Thin section cutting (1mm)

For factor peak current,

Corner cutting (radius 2mm)

For factor duration of pulse off time,

Table 5

Average factor for kerf performance

Factors

Level 1

Level 2

Level 3

TON

*-49.49

-49.63

-49.59

TOFF

*-49.53

-49.57

-49.61

IP

*-49.56

-49.57

-49.58

WS

-49.59

*-49.51

-49.61

Note: * factor level at optimum condition or the highest value

Table 6

Average factor for thin section cutting (1mm)

Factors

Level 1

Level 2

Level 3

TON

*-30.49

-30.52

-31.97

TOFF

*-30.75

-31.18

-31.04

IP

-32.32

*-30.12

-30.52

WS

-31.88

-31.55

*-29.54

Note: * factor level at optimum condition or the highest value

Table 7

Average factor for corner cutting (radius 2mm)

Factors

Level 1

Level 2

Level 3

TON

*13.738

12.986

11.35

TOFF

11.73

13.153

*13.191

IP

11.046

12.991

*14.036

WS

*13.65

11.827

12.597

Note: * factor level at optimum condition or the highest value

From the S/N ratio responses in Table 5-7, the best combination parameters can be determined by selecting the level with the highest value of each factor. Thus, the result for kerf is TON(1), TOFF(1),IP(1),WS(2); for thin section cutting is TON(1), TOFF(1),IP(2),WS(3); and for corner cutting is TON(1), TOFF(3),IP(3),WS(1).

8.1 Estimate the optimum value on performances

The optimum values for each response were estimated according to the optimal levels of parameters combination from Table 5-7. The example calculations are shown below done for kerf. Apply with the same equation to calculate optimum value for thin section and corner cutting. The estimation values can be summarized in Table 8.The percentage error between predict value and actual value for three responses are less than 10%. This verification test shows the whole experiment considered as valid.

For kerf performance

i) Grand average

Note: m = Total number of average factor effect

ii) Total contribution

Note: * = Factor levels at optimum condition

iii) Predict optimum value

Table 8

Summarize estimate optimum value prediction with actual value performances result

Estimate value

Actual value

% Error

Kerf

-49.57

0.1821

-49.39

294.71mm

288.33mm

2.16

Thin section cutting (1mm)

-30.99

3.061

-27.93

1024.9µm

963.33 µm

6.0

Corner cutting (radius 2mm)

12.69

2.766

15.457

2.1687mm

1.9857 mm

8.44

8.2 Analysis of variance (ANOVA)

The data in Table 9-10 shown result from analyze using ANOVA for kerf, thin section and corner cutting respectively. The relative percentage contribution among the factors is determined by comparing their relative variance. The ANOVA will compute the quantities such as degrees of freedom, sums of square, variance, F-ratio, pure sum of square and percentage contribution. The examples calculations of these quantities are shown below for kerf performance. Then, repeating with use the same equation for thin section and corner cutting.

For kerf performance

Total degree of freedom (f)

N = Total number of result

For factor TON

k = the number of levels for factor

For error

Sum of square (S)

Total sum of square (ST)

Correction factor (CF)

Sum of square for factor TON

Sum of square for error

Variance

For factor TON

For error

F-ratio (F)

For factor TON

Percentage contribution (P)

For factor TON

Table 9

ANOVA table for performance of kerf

Factors

f

S

V

F

P (%)

Pulse on time, TON

2

0.0287

0.0144

0

53.85

Pulse off time, TOFF

2

0.0090

0.0045

0

16.80

Peak current, IP

2

0.0008

0.0004

0

1.44

Wire speed, WS

2

0.0149

0.0074

0

27.91

Pooled error

0

0

0

Total

8

0.0534

100

Table 10

ANOVA table for performance of thin section cutting (1mm)

Factors

f

S

V

F

P (%)

Pulse on time,TON

2

4.2986

2.1493

0

19.17

Pulse off time,TOFF

2

0.2914

0.1457

0

1.30

Peak current, IP

2

8.2383

4.1192

0

36.74

Wire speed, WS

2

9.5971

4.7985

0

42.80

Pooled error

0

0

0

Total

8

22.425

100

Table 11

ANOVA table for performance of corner cutting (radius 2mm)

Factors

f

S

V

F

P (%)

Pulse on time, TON

2

8.9421

4.4711

0

28.00

Pulse off time, TOFF

2

4.1594

2.0797

0

13.02

Peak current, IP

2

13.8155

6.9077

0

43.25

Wire speed, WS

2

5.0236

2.5118

0

15.73

Pooled error

0

0

0

Total

8

31.941

100

From Table 9-11, the last column of the ANOVA table indicates the percentage contribution of each factor for kerf, thin section and corner cutting. The result in the table shows for kerf, that significant factors are TON is 53.85%, WS is 27.91% and TOFF is 16.80%. The peak current (IP) is not a significant factor which only contribute 1.44%. While for thin section cutting, that significant factors are WS is 42.80%, IP is 36.74%, and TON is 19.17%. But TOFF is 1.30% indicate as not a significant factor. For corner cutting, all factors are significant with IP is 43.25%, TON is 28%, WS is 15.73% and TOFF is 13.02%.

9. Conclusion

This research was focused on application of Taguchi optimization technique to find the optimum levels of parameters used in WEDM for accuracy study.

The optimum parameters combination for minimize kerf are: TON(1)(3µs), TOFF(1)(10 µs),IP(1)(5A) and WS(2)(100mm/min).

The optimum parameters combination for thin section cutting are: TON(1)(3µs), TOFF(1) (10 µs),IP(2)(10A) and WS(3)(150mm/min).

The optimum parameters combination for corner cutting are: TON(1)(3µs), TOFF(3)(18µs),IP(3)(15A) and WS(1)(50mm/min).

Among these factors, the pulse on time (TON) and wire speed (WS) is the most effective factors effect on machining accuracy for kerf, thin section and corner cutting.

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