Comparative Study of Electrode Wear Estimation in Wire EDM using Multiple Regression Analysis and Group Method Data Handling Technique for EN-8 and EN-19 

Abstract

 Wire Electrical Discharge Machining (WEDM) is a specialized thermal machining process capable of accurately machining parts with varying hardness or complex shapes, which have sharp edges that are very difficult to be machined by the main stream machining processes. In WEDM a specific wire run-off speed is applied to compensate wear and avoid wire breakage. Since the workpiece generally stays stationary and short discharge durations are applied, the relative displacement between wire and workpiece during one single discharge is very small. This study outlines the development of model and its application to optimize WEDM machining parameters using the Taguchi's technique which is based on the robust design. Present study outlines the electrode wear estimation in the wire EDM. EN-8 and EN-19 was machined using different process parameters based on L'16 orthogonal array. Among different process parameters voltage and flush rate were kept constant. Parameters such as bed speed, current, pulse-on and pulse-off was varied. Molybdenum wire having diameter of 0.18 mm was used as an electrode. Electrode wear was measured using universal measuring machine. Estimation and comparison of electrode wear was done using multiple regression analysis and group method data handling technique. From the results it was observed that, measured electrode wear and estimated electrode wear correlates well with respect to MRA than GMDH

Authors and Affiliations

G. Ugrasen , H. V. Ravindra , G. V. Naveen Prakash , D. L. Vinay

Keywords

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  • EP ID EP132205
  • DOI 10.9756/BIJIEMS.6022
  • Views 124
  • Downloads 0

How To Cite

G. Ugrasen, H. V. Ravindra, G. V. Naveen Prakash, D. L. Vinay (2014). Comparative Study of Electrode Wear Estimation in Wire EDM using Multiple Regression Analysis and Group Method Data Handling Technique for EN-8 and EN-19 . Bonfring International Journal of Industrial Engineering and Management Science, 4(2), 108-114. https://europub.co.uk/articles/-A-132205