Alireza Rashidi Komijan; Ahmad Masoudifar
Volume 1, Issue 4 , February 2021, , Pages 383-402
Abstract
Purpose: One of the most critical issues in supplying equipment and managing spare parts for power plant industries is evaluating and selecting suppliers and assigning orders to them. This study aims to achieve a comprehensive model for ranking the suppliers, classifying the parts, evaluating suppliers, ...
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Purpose: One of the most critical issues in supplying equipment and managing spare parts for power plant industries is evaluating and selecting suppliers and assigning orders to them. This study aims to achieve a comprehensive model for ranking the suppliers, classifying the parts, evaluating suppliers, and optimal allocation of orders. Methodology: The indicators of the supplier's evaluation were determined in the first stage. The weight of evaluation indicators was calculated by taking experts' opinions and using Group AHP and Minimum squares techniques. Prioritization and grouping of parts were done by sampling the Kraljic matrix, and the priority factor for each part was determined. In the second stage, using the TOPSIS technique, the rank of each supplier in terms of supplying the potential parts was determined. In the third stage, designing a mathematical model of planning the correct number zero-one was considered. The function of the target is to maximize the value of the purchase and include the restrictions of zero-one planning, limited budget, and management policies. GAMS software was used to solve the model. Findings: The results show that determining the group for each part, considering the two dimensions of supply risk and the vitality of the part provides a suitable management tool for equipment supply management. The zero and one integer planning model is appropriate for order allocation problems. In spare parts, the structure and components of the objective function and constraints can be changed according to the type of organization. Originality/Value: The TOPSIS technique properly combines the weight of evaluation indicators and expert opinions about the suppliers of each component, and the results can be used confidently in the design of the mathematical model.
