Abstract
Proper inventory control is challenging for supply chain management, especially under fluctuating and unpredictable demand. Complex distribution networks make the problem even more difficult. Despite a lot of inventory control methods have been developed, the Min–Max policy is still one of the most often implemented method in enterprise resource planning systems. The standard approach is however fairly static and ineffective for controlling stocks with high variability in demand. In this paper we propose a decision rules based approach to improve the efficiency of the Min–Max method through dynamic adjustment of the Min–Max ordering levels. The implementation of the improved Min–Max method in a company from the automotive industry resulted in a significant increase of company’s sales volume. Thanks to the use of decision rules the proposed approach is flexible enough to complement other existing methods for inventory management, making it possible to automate inventory control processes, even in a complex and dynamic environment.
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