Optimization of the quality and productivity characteristics of AISI P20 tool steel in EDM process using PCA-based grey relation analysis

In the recent years, there is a growing demand for new manufacturing technologies to meet the productivity and quality requirement in the industries. Electro discharge machining (EDM) is one of the most versatile machining processes due to its capability to generate complex shapes particularly on difficult-to-cut materials. In the present work, L 18 OA based on Taguchi experimental design is used to study the effect of various EDM process parameters like discharge current (Ip), pulse on time (T on ), duty cycle (T au ) and polarity (straight and reverse) on material removal rate (MRR), surface roughness (SR) and surface crack density (SCD).A hybrid methodology consisting of principal component analysis (PCA) combined with grey relation analysis (GRA) has been adopted in order to simultaneously optimize various EDM parameterswith an aim to achieve reasonably low value of SCD and SR and high value of MRRduring EDM of AISI P20 tool steel usingbrass electrode. Keyword: Grey relation analysis, Principal component analysis,Electro discharge machining, Multi-objective optimization.