Materials Selection Using a 2-tuple Linguistic Multi-criteria Method

Abstract

The materials selection can affect the design component radically, with effect on the manufacturing systems efficiency, environmental impact issues, and customer satisfaction. There are different methods employed for materials selection; however, two steps are usual for most of these methods: screening and ranking. The ranking step identifies among materials candidates those that can perform the function the best as possible. Multi-criteria methods have been widely employed to materials selection, especially in the ranking step. Most of these methods take advantage of fuzzy numbers and linguistic variables to process qualitative information and information with uncertainties. One of the approaches that have been developed to solve issues related to make decisions in multi-criteria methods using linguistic information is the 2-tuple linguistic computational model. The main advantage of this approach is taking the "loss of information" away, which provides a higher precision on results. This paper aims to present a multi-criteria method for materials selection ranking step based on 2-tuple linguistic variables. The steps and several equations needed to apply the proposed method are described. Two case studies are presented and compare results with other methods to demonstrate the proposed method potential.

A Multi-Criteria Model for the Techno-Economic Evaluation of Fat Removal Technologies From Dairy Waste

“…A sensitivity analysis was performed to illustrate the effectiveness and robustness of the TOPSIS 2-tuple method for selecting and ranking the most suitable technologies for separating fat from dairy waste. The results derived by the TOPSIS 2-tuple method with those deduced by VIKOR 2-tuple (Wu et al, 2015) and TARGET 2-tuple (Setti et al, 2019) are shown in Table 4.…”

“…Decision-makers determine each criterion's importance, that is, the weights of the criteria through a set of linguistic variables. The aggregate linguistic weight of the criteria is obtained by Equation ( 5), and the weight of the criteria in the form of real numbers is obtained by Equation ( 6) as proposed by (Setti et al, 2019).…”