1- Department of Industrial Engineering, Faculty of Engineering, University of Kashan, Kashan, Iran , dehnavi@kashanu.ac.ir
2- Department of Industrial Engineering, Faculty of Engineering, University of Kashan, Kashan, Iran
Abstract: (287 Views)
The selection of material handling equipment is crucial for companies as it significantly impacts productivity in manufacturing and service operations. This decision-making process involves multiple criteria that are often conflicting and cannot be easily compared. To address this complexity, a multi-criteria decision-making framework is employed, where experts' preferences and criteria weights are expressed using fuzzy numbers, such as trapezoidal or triangular fuzzy numbers. The fuzzy VIKOR methodology is then utilized to rank the alternatives based on the aggregate fuzzy values of ratings and weights. A Monte Carlo simulation and a centroid method are employed to derive a suitable shape and obtain a precise value. This additional step enhances the robustness and accuracy of the decision-making process. To demonstrate the effectiveness of this approach, a case study is conducted at R.S-Arvin, a manufacturing company. By applying the proposed methodology to a real-world scenario, the study showcases how it can be used to make informed decisions in practical settings. The results obtained from this case study highlight the benefits of incorporating fuzzy logic and simulation techniques in material handling equipment selection processes. Overall, this research contributes to advancing decision-making practices in companies by providing a systematic and comprehensive approach that considers multiple criteria and uncertainties inherent in such complex systems. The integration of fuzzy logic and defuzzification methods (simulation and centroid method) offers a practical solution for addressing real-world challenges related to equipment selection and optimization in manufacturing environments.
Type of Study:
Research |
Subject:
Operations Research Received: 2024/08/6 | Accepted: 2025/03/5