Application of MCDM and Taguchi super ranking concept for materials selection problem

Abstract

Material selection is a topic of pivotal importance in the optimal design and development of industrial products. Increasing demand for high-performance materials with desirable and tailor-made properties is expected to drive the future market. This paper examines the application of multicriteria decision-making techniques like AHP, TOPSIS, EDAS, VIKOR, and Taguchi-based super ranking concepts for the selection of optimal aluminum alloy material for the sheet metal forming process. The criteria used to evaluate the optimal material selection were identified as yield strength, tensile strength, thermal conductivity, impact, density, specific heat, coefficient of thermal expansion, and % elongation. The most ranked aluminum material frequency is selected for sheet metal forming simulation using DEFORM, a process simulation FEM-based tool. An integrated Taguchi DOE and process simulation were carried out for the best-ranked AA2024 aluminum material. The results showed that the MCDM and Taguchi-based super ranking concept provides an intelligent and methodical assessment for solving material selection from a finite set of alternatives for the sheet metal forming process. The group decision behavior, agility, and flexibility in including multiple decision-making criteria for overall comparative analysis of materials, and manufacturing processes with uncertainty make MCDM methods a definitive tool for materials and manufacturing process selection.