Multicriteria Decision Making on 3D printers for economic manufacturing using Neutrosophic environment

作     者：Nagarajan, D. Gobinath, V.M. Broumi, Said 

作者机构：Department of Mathematics Rajalakshmi Institute of Technology Tamil Nadu Chennai India Department of Mechanical Engineering Rajalakshmi Institute of Technology Tamil Nadu Chennai India Laboratory of Information Processing Faculty of Science Ben M’Sik University Hassan II B.P 7955 Sidi Othman Casablanca Morocco 

出 版 物：《Neutrosophic Sets and Systems》 (Neutrosophic Sets Syst.)

年 卷 期：2023年第57卷

页      面：33-56页

核心收录：

主　　题：Decision support systems 

摘      要：Multicriteria group decision-making scenarios with a large number of criteria values may be challenging for experts to control. This is a result of the specialists need to consider an excessive amount of data. They find it difficult to make the optimal decision since the possibilities overwhelm them. We propose a novel multicriteria group decision-making method that methodically eliminates the initial set of criterion values in order to address this issue. One of the most promising emerging technologies currently in development is an additive manufacturing (AM), which includes 3D printing. It has been hypothesized that 3D printing technology could eventually replace the conventional production machinery that is commonly used in the industrial sector. Making conclusions through accurate figures is difficult for decision-makers due to the complexity and ambiguity of reality. Neutrosophic ensembles are used to tackle uncertainty and indeterminacy in a practical environment. By concentrating on ranking the smaller set of criterion values, the proposed method enables the experts to carry out the group decision-making process. As a result, a relaxed decision-making environment is created, allowing the experts to handle a reasonable amount of information while still making decisions. To demonstrate the decision process of a 3D printer, we combine a single valued Neutrosophic with hybrid score and accuracy function, the single valued Neutrosophic number ranking approach, and the single valued Neutrosophic score and accuracy function. To determine the best attributes, the score function was used to rank the total values of each possibility. Concrete examples have been given to support the suggested solution to the multi-attribute decision-making problem (MADM). © (2023). All Rights Reserved.