Novel Multi-objective Decision-Making and Trade-Off Approach for Selecting Optimal Machining Parameters of Inconel-800 Superalloy

Abstract

Inconel-800 is a superalloy having moderate strength, sufficient resistance to oxidation at high temperature and carburization. Work hardening nature of the material makes it very hard to machine using traditional methods. Wire-cut electrical discharge machining (WEDM) is most widely applied for difficult-to-machine materials because of its capability to produce jobs with minute accuracy and precision. Time taken to process job is the major drawback of the WEDM technique. Therefore, the need arose for formulating a stable predictive model which reduces human effort and maximizes production. The comprehensive intention of this study is to develop robust and stable multi-objective decision-making and soft computing models for selecting the best machining parameters and forecasting the machining performance of Inconel-800 superalloy. Taguchi’s method is applied for designing the experimental phase of the study. The computational part is a three-stage process. The first stage is selecting the best machining parameters of WEDM by multi-criteria decision-making (MCDM) technique. A novel MCDM technique is proposed that is based on the concept of risk minimization. The second stage involves the formulation of predictive model using soft computing technique like response surface methodology (RSM). The performance of the technique was scrutinized on a statistical platform to check the gullibility of the model. The final stage is the trade-off analysis by multi-objective RSM (MORSM) which strategically draws balance among the multiple outputs of the problem. Finally, the proposed MCDM and MORSM models are applied for selecting the best and optimal combination of machining Inconel-800 by WEDM technique.