Taguchi based utility and grey relational approaches to optimize bi-objective machining of AISI 202 stainless steel

Abstract

To optimize single response problems traditional Taguchi approach is widely used. Performance evaluation of the manufacturing process is often determined by several quality characteristics. Under such circumstances, multi-characteristics response optimization is the solution to optimize multi-objective quality characteristics. In the present work, bi-objective characteristics response optimization model based on Taguchi based Grey relational analysis and Utility approach is used to optimize process parameters, cutting speed, depth of cut, feed and nose radius on two different performance characteristics namely surface roughness (Ra) and material removal rate (MRR) during dry turning of austenitic stainless steel AISI 202 with cemented carbide tipped tool. Both approaches are analysed using Taguchi’s L8 orthogonal array (OA) and found that both approaches predicted the same experimental settings, higher levels of cutting speed, depth of cut, nose radius and lower level of feed are critical to achieve low surface roughness and high material removal rate simultaneously.