Synergizing neutrosophic logic with Entropy-VIKOR of MCDM for superior AWR robot selection in manufacturing
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...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
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| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025026155 |
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| Summary: | 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 the prospective criterion weights determined using the entropy method 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. |
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| ISSN: | 2590-1230 |