A fuzzy based decision model for nontraditional machining process selection

Abstract

Manufacturing systems are processes in which inputs obtained from interior and exterior sources are transformed into an output by gathering inputs in an optimal way to guide the enterprises. Machining process plays a critical role in industry, and thus, directly affects the efficiency of the manufacturing systems. Due to different importance of the conflicting criterions, the multi-criteria decision-making methods are extremely useful in the selection process of the proper machining type. This study provides distinct systematic approaches in fuzzy and crisp environments to deal with the selection problem of proper machining process and proposes a decision support model for the guidance of decision makers to assess potentials of seven distinct nontraditional machining processes, namely laser beam machining, plasma arc machining, water jet machining, abrasive water jet machining, electrochemical machining, electrical discharge machining (EDM), and wire–EDM in the cutting process of carbon structural steel with the width of plate of 10 mm. The required data for decision and weight matrices are obtained via a questionnaire to specialists, as well as by deep discussions with experts and making use of past studies. Finally, an application of the proposed model is also performed via the SETED 1.0 software to show the applicability of the model.