Essay: Wire Electrical Discharge Machining

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  • Wire Electrical Discharge Machining
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Wire Electrical Discharge Machining is a Manufacturing process whereby a desired shape is obtained using electrical discharges by repeated spark cycle Machining parameters are provided in table by the machine tool manufacturers often do not meet the operator requirements. Selection of optimum machining and its machining parameters combinations is needed for obtaining higher cutting efficiency and accuracy.

Each experiment have been performed under different cutting conditions of gap voltage, pulse OFF time, and pulse ON time and Wire feed. Wire speed, wire tension, resistance, dielectric fluid pressure and cutting length are taken as fixed parameters. AISI52100 was selected as a work material to conducts the experiments.

From experimental results and obtained database the surface roughness was determined for each machining performance criteria. Signal to noise ratio or (S/N) ratio was applied to measure the performance characteristics deviating from the actual value. Finally, experiments confirmation was carried out to identify the effectiveness of this proposed method.

ABSTRACT

With the start of globalization there are many companies emerges to sustain this competitive market. We are to make product which has less price. In current situation material removal rate (MRR) and surface roughness (SR) are most important parameters to make the product more economical. To find out relation of parameters, and we can get maximum material removal rate (MRR) and less surface roughness (SR).

CHAPTER: 1 INTRODUCTION

1.1 Wire cut EDM

The Wire cut electro discharge machine that is uses CNC movement to produce the desired contour and shape. It does not require a special shaped electrode, instead it uses continuous traveling vertical wire under tension as the electrode
The electrode in wire cut electro discharge machine is about as thick as a small diameter needle whose path is controlled by the computer to produce the shape required.
A continuous travelling wire electrode the diameter of a small needle or less is controlled by the computer to follow a programmed path to cut a narrow slot through the work piece to producethe required shape.

Fig. 1.1Wire cut EDM
In wire cut EDM, a thin single strand metal wire generally made of brass which fed through the work piece and submerged in a tank of dielectric fluid it means distilled water. The wire does not touch the work piece so there is no physical pressure on the work piece compared to milling cutters and grinding wheels.
This process is used to cut plates are thick as 300mm and to make dies tools, punches and from hard metals that are too difficult to machine with other methods. The wire which is constantly fed from a spool is held between lower guides upper and lower.
1.2 PRINCIPLE OF WIRE CUT EDM
In wire electro discharge machine the conductive materials are machined with a series of electrical sparks that are produced between the work piece and moving wire. High frequency pulses of alternating current or direct current is discharged from the wire to the work piece with in a very small spark gap through insulated distilled water.
More numbers of sparks can be observed at one time. The volume of metal removing during this short period of spark discharge depends on the desired cutting speed and the required surface finish. These chips are flushed away from the cut with a stream of distilled water passing through the top and bottom flushing nozzles. This water also prevents heat build-up in the work piece. Without this cooling, thermal expansion of the part would affect positional accuracy and size of work piece. Keep in mind that it is the OFF and ON time of the spark that is repeated over and over that removes material.
1.3 OPERATING PARAMETERS
Machine Parameters:
1. Table feed. 2. Pulse on time. 3. Pulse off time. 4. Flushing
Wire Parameters:
1.Material of wire. 2. Diameter of wire. 3. Wire speed. 4. Wire tension.

1.4 OBJECTIVE
1. To determine significant parameters affecting the performance of machining.
2. To discuss the cause effect relationship of machining parameters and the performance in WEDM
3. To Minimize the Surface Roughness, kerf width and Maximize MMR by taking optimize values of input Wire Cut EDM Parameters.
4. To identify the most effective parameter for response

CHAPTER: 2 LITERATURE REVIEW

1. Brajesh Kumar Lodhi, Sanjay Agarwal (2014)

“Optimization of machining parameters in WEDM of AISI D3 Steel using Taguchi Technique.”

2. Mu-Tian Yan, Yi-TingLiu (2009)
“Design, analysis and experimental study of a high-frequency power supply for finish cut of wire-
EDM.”
3. G. Selvakumar, G. Sornalatha, S. Sarkar, S. Mitra (2014)
“Experimental investigation and multi-objective optimization of wire electrical discharge machining (WEDM) of 5083 aluminum alloy.”

CHAPTER: 3 METHODOLOGY
Table 3.1- L32 orthogonal array
No Pulse on time (µs) Pulse off time (µs) Voltage (V) Wire feed (mm/sec)
1 90 40 22 6
2 90 40 26 9
3 90 40 30 12
4 90 40 34 15
5 90 50 22 6
6 90 50 26 9
7 90 50 30 12
8 90 50 34 15
9 90 60 22 9
10 90 60 26 6
11 90 60 30 15
12 90 60 34 12
13 90 70 22 9
14 90 70 26 6
15 90 70 30 15
16 90 70 34 12
17 110 40 22 15
18 110 40 26 12
19 110 40 30 9
20 110 40 34 6
21 110 50 22 15
22 110 50 26 12
23 110 50 30 9
24 110 50 34 6
25 110 60 22 12
26 110 60 26 15
27 110 60 30 6
28 110 60 34 9
29 110 70 22 12
30 110 70 26 15
31 110 70 30 6
32 110 70 34 9

ANALYSIS OF VARIANCE (ANOVA)
The main effects indicate the general trends of the influence of the factors. The optimum condition is identified by studying the main effects of each of the factors. Higher or lower value produces the preferred results, the level of the factors, which are expected to produce the best results can be predicted.
SIGNAL TO NOISE RATIO
To calculate the signal to noise ratio, experiments are conducted in a systematic manner. Experiments are organized according to orthogonal arrays.
Noise factors are changed in a balanced fashion during experiments. The characteristic of signal to noise ratio can be divided into three categories smaller is better, Higher is better and nominal is best when the characteristic is continuous. These characteristics are selected as per objective of problem.
GREY RELATIONAL ANALYSIS
The grey relational analysis, a grey relational grade can be obtained to evaluate the multiple performance characteristic. As a result, optimization of the complicated multiple performance characteristic can be converted into the optimization of a single grey relation grade. For multiple performance characteristic optimizations using GRA, following steps are followed:
1. Conduct the experiments of different settings of parameters based on OA.
2. Normalization of experimental result for all performance characteristics.
3. Performance of grey relational generating and calculation of grey relational coefficient (GRC).
4. Calculation of grey relation grade using weighing factor for performance characteristics.
5. Analysis of experimental results using GRG and statistical analysis of variance (ANOVA).
6. Selection of optimal levels of process parameters.
7. Conducting confirmation experiment to verify optimal process parameter settings.

CHAPTER 4:ANALYSIS AND DISCUSSION
4.1 EXPERIMENTAL RESULTS
Table 4– Experimental Readings
No Ton(µs) Toff (µs) voltage WF(mm/sec) MRR(mm3/min) SR(µm) KW (mm)
1 90 40 22 6 4.865 2.86 0.421
2 90 40 26 9 4.526 2.75 0.41
3 90 40 30 12 4.325 2.56 0.35
4 90 40 34 15 4.235 2.45 0.32
5 90 50 22 6 4.658 2.79 0.431
6 90 50 26 9 4.3547 2.56 0.392
7 90 50 30 12 4.258 2.42 0.372
8 90 50 34 15 4.125 2.39 0.301
9 90 60 22 9 4.356 2.68 0.452
10 90 60 26 6 4.265 2.54 0.401
11 90 60 30 15 4.125 2.5 0.385
12 90 60 34 12 3.998 2.41 0.325
13 90 70 22 9 4.235 2.52 0.465
14 90 70 26 6 4.012 2.39 0.421
15 90 70 30 15 3.998 2.29 0.401
16 90 70 34 12 3.879 2.25 0.382
17 110 40 22 15 5.989 2.98 0.4562
18 110 40 26 12 5.865 2.87 0.423
19 110 40 30 9 5.758 2.69 0.364
20 110 40 34 6 5.458 2.59 0.342
21 110 50 22 15 5.3568 2.84 0.456
22 110 50 26 12 5.2654 2.74 0.423
23 110 50 30 9 5.1258 2.56 0.392
24 110 50 34 6 5.0125 2.35 0.335
25 110 60 22 12 5.3256 2.71 0.476
26 110 60 26 15 5.286 2.61 0.423
27 110 60 30 6 5.198 2.49 0.402
28 110 60 34 9 5 2.32 0.35
29 110 70 22 12 5.246 2.65 0.472
30 110 70 26 15 5.1985 2.45 0.442
31 110 70 30 6 4 2.21 0.425
32 110 70 34 9 4.258 2.02 0.392

Main Effects Plot for SNR of material removal rate
The main effects plot for S/N ratio of material removal rate versus pulse on , pulse off, wire speed and voltage are shown in fig.4.3.1, which is generate from the value of S/N ratio of material removal rate as per table in minitab-16 statistical software is useful to find out optimum parameter value for response variable.
Fig.4.3.1 shows that higher material removal rate will meet at pulse on 110µs, pulse off 40µs, voltage 22 volt and wire speed 15 mm/sec. The graph generate by use of minitab-16 statistical software for material removal rate is shown in fig.4.3.1

Fig 4.3.1- Effect of control factor on material removal rate
From the fig.4.3.1, it has been conclude that the optimum combination of each process parameter for higher material removal rate is meeting at high pulse on time [A2], low pulse off time [B1], low voltage [C1] and low wire speed [D4].
4.3.2 Main Effects Plot for SNR of Surface roughness
Fig.4.3.2 shows that lower Surface roughness will meet at pulse on time 90 µs, pulse off 70 µs, voltage 34 volt and wire speed 9 mm/sec From the fig.4.3.2, it has been conclude that the optimum combination of each process parameter for lower surface roughness is meeting at pulse on time [A1], pulse off time [B4], voltage [C4] and wire speed [D2].

Fig.4.3.2- Effect of control factor on Surface roughness
4.3.3 Main Effects Plot for SNR kerf width
Fig.4.3.3 shows that lower kerf width will meet at pulse on time 90µs, pulse off 40µs, voltage 34 volt and wire speed 15 mm/sec. From the fig.4.3.3, it has been conclude that the optimum combination of each process parameter for lower kerf width is meeting at pulse on time [A1], pulse off time [B1], voltage [C4] and wire speed [D4].

Fig. 4.3.3- Effect of control factor on kerf width

CHAPTER : 5 CONCLUSION

Experimental investigation on wire electrical discharge machining of AISI52100 has been done using brass wire of 0.25mm. The following conclusions are made.
1. From the S/N ratio plot the optimum parameter settings for material removal rate at, ie. Ton = 110 µs, Toff = 40 µs, Voltage = 22 V and wire speed = 15 mm/sec.
2. It can also observed that Ton, Toff and Voltage is the most prominent factor affecting the Material removal rate.
3. From the S/N ratio plot the optimum parameter setting for surface roughness at, ie. Ton = 110 µs, Toff = 70 µs, Voltage = 34 V and wire speed = 9 mm/sec.
4. From the S/N ratio plot the optimum parameter setting for surface roughness at, ie. Ton = 90 µs, Toff = 50 µs, Voltage = 34 V and wire speed = 15 mm/sec.
5. Based on the Grey relational analysis, the optimized input parameter combinations to get all responses like maximum material removal rate, the minimum surface roughness and the minimum kerf width are pulse on time 110 µs, pulse off time 40 µs, Voltage 22 V and wire speed 15 mm/sec.

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