Grey Relational Analysis Coupled with Principal Component Analysis for Optimization Design of the Machining Parameters in Electro-Discharge Diamond Face Grinding

Electro-Discharge Diamond Grinding (EDDG), a hybrid machining process comprising diamond grinding and electrodischarge grinding, has been developed for machining of electrically conductive difficult-to-machine very hard materials. The process employs simultaneous synergetic interactive effect of abrasion action and electro-discharge action. A self-designed face grinding setup is attached on ELEKTRA PULS EDM machine to use it as Electro-Discharge Diamond Face Grinding (EDDFG). This paper investigates optimization design of an EDDFG process performed on high speed steel (HSS).The major performance characteristics selected to evaluate the processes are material removal rate (MRR) and wheel wear rate (WWR), and the corresponding EDDFG parameters are wheel RPM, current, pulse ontime and duty factor. In this study, since the process is with multiple-performance characteristics, therefore, the grey relational analysis that uses grey relational grade as performance index is specially adopted to determine the optimal combination of EDDFG parameters. Moreover, the principal component analysis is applied to evaluate the weighting values corresponding to various performance characteristics so that their relative importance can be properly and objectively described. The results of confirmation experiments reveal that grey relational analysis coupled with principal component analysis can effectively be used to obtain the optimal combination of EDDFG parameters. Hence, this confirms that the proposed approach in this study can be a useful tool to improve the machining performance of EDDFG process.