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Optimization of WEDM Process using Taguchi Utility Analysis


Affiliations
1 School of Mechanical Engineering, VIT University, Vellore – 632014, Tamil Nadu, India
 

This research paper focused on development of a multi response optimization technique, using traditional utility – Taguchi method in conjunction with the principal component analysis for weight assignment concept in Wire Electrical Discharge Machining (WEDM). Inconel-825 super alloy has been selected as work material for experimentation. The effect of process parameters such pulse on time (TON), pulse off time (TOFF), Corner Servo voltage (CS), flushing pressure (WP), Wire Feed (WF), Wire Tension (WT), Spark Gap Voltage (SV) and Servo Feed (SV) were investigated on Material Removal Rate (MRR), Surface Roughness (SR) and Spark Gap (SG) in WEDM operation. Further, the responses such as MRR, SR and SG were modelled empirically through regression analysis. The optimization of multiple responses has been done for satisfying the requirements of industrial users, in contrast to the traditional multi-response techniques. Finally, confirmation experiment was performed to validate the effectiveness of the proposed optimal condition.
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  • Optimization of WEDM Process using Taguchi Utility Analysis

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Authors

G. Rajyalakshmi
School of Mechanical Engineering, VIT University, Vellore – 632014, Tamil Nadu, India

Abstract


This research paper focused on development of a multi response optimization technique, using traditional utility – Taguchi method in conjunction with the principal component analysis for weight assignment concept in Wire Electrical Discharge Machining (WEDM). Inconel-825 super alloy has been selected as work material for experimentation. The effect of process parameters such pulse on time (TON), pulse off time (TOFF), Corner Servo voltage (CS), flushing pressure (WP), Wire Feed (WF), Wire Tension (WT), Spark Gap Voltage (SV) and Servo Feed (SV) were investigated on Material Removal Rate (MRR), Surface Roughness (SR) and Spark Gap (SG) in WEDM operation. Further, the responses such as MRR, SR and SG were modelled empirically through regression analysis. The optimization of multiple responses has been done for satisfying the requirements of industrial users, in contrast to the traditional multi-response techniques. Finally, confirmation experiment was performed to validate the effectiveness of the proposed optimal condition.

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DOI: https://doi.org/10.17485/ijst%2F2018%2Fv11i23%2F114377