Eco-material selection using fuzzy TOPSIS method

In the classical multiple attribute decision-making or MADM methods, the ratings and the weights of the criteria are known precisely. However, in eco-material selection exercises, the available data are typically inadequate because of the selection dual quantitative and qualitative natures. Some of the qualitative selection criteria can be rated in several classes rather being expressed by exact numerical values; hence the application of fuzzy concepts in decision-making seems attractive to deal with such kind of ratings. Thusly, the presented study attempts to propose an eco-material selection approach specific to the automobile body panels using a fuzzy technique for order preference by similarity to ideal solution (TOPSIS), to incorporate both numerical and rating-based criteria into one holistic sustainability model. TOPSIS and fuzzy logic can aid the material selection process in translating the design goals and parameters into usable numbers that in turn can be used to rank candidate materials in their closeness to the ideal solution. An additional uniqueness of this study stems from using the fuzzy-TOPSIS as a scoring tool without any assigned weights for the different selection attributes, in order to avoid the bias that is typically associated with other classical MADM, such as quality function deployment, analytical hierarchy process and digital logic.