Synergizing neutrosophic logic with Entropy-VIKOR of MCDM for superior AWR robot selection in manufacturing

摘要

The selection of industrial robots is a crucial decision-making process that significantly impacts the efficiency and competitiveness of manufacturing operations. With a wide range of robot options available in the market, selecting the most suitable robot for specific tasks requires a comprehensive evaluation of various criteria such as cost, performance, reliability, and compatibility with operational requirements.This study presents, a hybrid Multi-Criteria Decision-Making (MCDM) technique using Single Valued Neutrosophic Numbers to define the weight criteria and ranking alternatives using the Entropy-VIKOR (“VIseKriterijumsko Kompromisno Rangiranje”) method. This approach is used for selecting industrial arc welding robots. By utilizing single-valued neutrosophic numbers, the most suitable robot can be chosen for carrying out the required welding tasks efficiently and cost-effectively. with prospective criterion weights applied with the help of Entropy for subsequent analysis. The VIKOR approach prioritizes the alternatives based on the significance of criteria in the selection process. The proposed method for choosing robots was tested using real-world examples involving arc welding robots. Experts provided their evaluations for eight different robots, and the best option was identified using the combined SVN-Entropy–VIKOR approach. Sensitivity is supported by spearmans correlation for rank consistency and comparative analysis is conducted to prove the robustness of the applied MCDM techniques. • The study proposes a hybrid Multi-Criteria Decision-Making (MCDM) approach combining Single Valued Neutrosophic Numbers and the Entropy-VIKOR method for robot selection. • The methodology is specifically applied to the selection of industrial arc welding robots , addressing real-world manufacturing needs. • Single Valued Neutrosophic Numbers are employed to handle uncertainty and imprecision in expert evaluations during criteria weighting. • The entropy method is used to objectively determine the weight of each criterion before ranking the alternatives . • The proposed model is validated with expert input across eight robot alternatives, and sensitivity and comparative analysis confirm the robustness of the approach.