Application of grey correlation-based EDAS method for parametric optimization of non-traditional machining processes

Abstract

Higher dimensional accuracy along with better surface finish of various advanced engineering materials has turned out to be the prime desideratum for the presentday manufacturing industries. To this end, Non-Traditional Machining (NTM) processes have become quite popular because of their ability to produce intricate shape geometries on diverse difficult-to-machine materials. To allow these processes to operate at their fullest capability, it is often recommended to set their different input parameters at optimal levels. Thus, in this paper, a new technique combining grey correlation method with evaluation based on distance from average solution is applied for simultaneous optimization of three NTM processes, i.e., photochemical machining process, laser-assisted jet electrochemical machining process, and abrasive water jet drilling process. The derived optimal parametric combinations outperform those as identified by other popular multi-objective optimization techniques with respect to the considered response values. The results of analysis of variance also identify the most inuencing parameters for the said NTM processes. Finally, the developed surface plots would help the process engineers investigate the effects of different NTM process parameters on the corresponding grey appraisal scores.