Optimization of Surface Roughness and MRR in EDM Using WPCA

Das, Milan Kumar; Kumar, Kaushik; Barman, Tapan Kumar; Sahoo, Prasanta

doi:10.1016/j.proeng.2013.09.118

Cited by 34 publications

(16 citation statements)

References 10 publications

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“…Therefore, the electrical discharge machining (EDM) process has become a feasible method to machine the new hybrid metal matrix composites [21,22]. Most previous researchers [23][24][25] have experimented with AMCs and traditional MMCs coupled with EDM to achieve a high material removal rate (MRR) and low surface roughness (SR). Recently, the authors of [26][27][28] experimented with Al7075-based composite materials in EDM.…”

Section: Introductionmentioning

confidence: 99%

An Experimental Investigation on the Material Removal Rate and Surface Roughness of a Hybrid Aluminum Metal Matrix Composite (Al6061/SiC/Gr)

Singh

Garg

Maharana

et al. 2021

Metals

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The objective of this paper was to determine the optimum process parameters of an electric discharge machine while machining a new hybrid aluminum metal matrix composite. In this study, a new hybrid aluminum metal matrix composite was prepared, with silicon carbide and graphite particles used as reinforcements, with the help of the stir casting method. The selected electric discharge machining parameters in this study were peak current (I), voltage (V), pulse-on time (Ton), and tool material, while the response parameters were material removal rate and surface roughness. To machine the fabricated samples, two different types of tool materials (copper and brass) were used as electric discharge machine electrodes, and each had a diameter (Ø) of 12.0 mm. The optimal settings of the electric discharge machining parameters were determined through experiments planned, conducted, and analyzed using the Taguchi (L18) technique. An analysis of variance and confirmatory tests were used to check the contribution of each machining parameter. It was found that the material removal rate increased with the increase in pulse-on time and pulse current, whereas the material removal rate decreased with the increase in voltage. On the other hand, reduced surface roughness could only be achieved when current, voltage, and pulse duration were low. It was also found that the selected electric discharge machining electrodes had a significant effect on both the material removal rate and the surface roughness.

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Section: Introductionmentioning

confidence: 99%

An Experimental Investigation on the Material Removal Rate and Surface Roughness of a Hybrid Aluminum Metal Matrix Composite (Al6061/SiC/Gr)

Singh

Garg

Maharana

et al. 2021

Metals

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“…1 3 2 1 1 3 3 2 2 1 1 1 2 1 2 2 2 1 3 3 2 2 1 2 2 2 2 3 2 2 3 1 2 3 1 3 2 3 2 1 2 3 3 2 3 1 1 1 3 1 2 2 3 1 3 3 3 2 1 2 3 2 2 3 3 2 3 1 3 3 1 3 3 3 2 1 3 3 3 2 Taguchi Method -Weighted Principal Component Analysis (WPCA) In Taguchi method, optimization can only be done for one response only.To optimizemultiple response such as surface roughness and material removal rate simultaneously can be used the combination of Taguchi method and weighted principal component analysis (WPCA). The method is used to eliminate correlations between responses and to change the correlated response to an uncorrelated response index called the principal component (Das, 2013). The steps for the optimization process with Taguchi -weighted principal component analysis (WPCA) method can be seen in Figure 1.…”

Section: Design Experimentsmentioning

confidence: 99%

Optimization of Multiple Response Using Taguchi-WPCA In ST 60 Tool Steel Turning Process With Minimum Quantity Cooling Lubrication (MQCL) Method

Pamuji¹,

Wahid²,

Rohman³

et al. 2018

Aceh Int. J. Sci. Technol

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-A research was conducted for the optimization of the turning process ST 60 tool steel with multiple performance characteristics based on the orthogonal array with Taguchi-WPCA method. Minimum Quantity Cooling Lubrication (MQCL) method was applied as a coolant. The experimental studies were conducted by varying the cutting speed, feeding rate, depth of cut and type of coolant. The optimized multiple performance characteristics were surface roughnessand material removal rate. An orthogonal array, signal-to-noise ratio, grey relational analysis, weighted principal component analysis and analysis of variance were employed to study the multiple performance characteristics. Experimental results showed hat cutting speed gives the highest contribution inminimizing the surface roughness and maximizing the material removal rate, followed by feeding speed, type of coolant and depth of cut. The minimum surface roughness and maximum of material removal rate could be obtained by using the values of cutting speed, feeding speed, depth of cut and coolant of 172.95 m/minute, 0.053 mm/rev, 0.25 mm, and vegetable oil respectively.

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“…An increase in the discharge duration causes an increase in the material removal rate until it reaches a limit, after which any further increase leads to a decrease in the workpiece’s MRR. As the discharge duration gets longer, the energy effects are experienced for a longer period of time, making debris clearing and restoration of the dielectric fluid properties much more difficult [ 20 ].…”

Section: Introductionmentioning

confidence: 99%

Analysis of EDM Performance, through a Thermal–Electrical Model with a Trunk-Conical Discharge Channel, Using a Steel Tool and an Aluminium Workpiece

et al. 2021

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In this article, a finite element (FE) thermal–electrical model with a trunk-conical discharge channel is employed to simulate individual EDM discharges with a time-on of 18 μs up to 320 μs, which are subsequently compared with the experimental results to validate the model. The discharge channel is a trunk-conical electrical conductor which dissipates heat by the Joule heating effect, being the correspondent factor equal to 1. Instead of the usual copper–iron electrode combination, steel (DIN CK45) and aluminium alloys (DIN 3.4365) are the implemented materials on both the tool and the workpiece, respectively. The numerical results were measured using the melting temperature of the materials as the boundary of material removal. The results obtained with the thermal–electrical model, namely the tool wear ratio, the tool wear rate, the material removal rate, and the surface roughness, are in good agreement with experimental results, showing that the new FE model is capable of predicting accurately with different materials for the electrodes.

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Optimization of Surface Roughness and MRR in EDM Using WPCA

Cited by 34 publications

References 10 publications

An Experimental Investigation on the Material Removal Rate and Surface Roughness of a Hybrid Aluminum Metal Matrix Composite (Al6061/SiC/Gr)

An Experimental Investigation on the Material Removal Rate and Surface Roughness of a Hybrid Aluminum Metal Matrix Composite (Al6061/SiC/Gr)

Optimization of Multiple Response Using Taguchi-WPCA In ST 60 Tool Steel Turning Process With Minimum Quantity Cooling Lubrication (MQCL) Method

Analysis of EDM Performance, through a Thermal–Electrical Model with a Trunk-Conical Discharge Channel, Using a Steel Tool and an Aluminium Workpiece

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