Mrp systems considering fuzzy capacity, lead times and inventory availability

Abstract

This article aims to propose a fuzzy model for closed-loop material requirement planning (MRP) systems considering uncertain parameters like production capacity, on-hand inventory and lead times. For this, a deterministic closed-loop MRP model is proposed, and then fuzzy coefficients in the constraints of the model are used to establish the fuzzy MRP model, which depends on the degrees of satisfaction (λ) of the decision-maker. Data from a production plan of a company dedicated to the manufacture of electrical transformers are employed to verify the proposed fuzzy MRP model, minimizing inventory holding costs, production setup costs, and extra capacity costs. The results show the fuzzy model performs better than the deterministic model, especially for low λ values, providing better performance in terms of the total cost, total inventory, service level, and computational efficiency.