Inventory control of spare parts using a Bayesian approach: A case study

This paper presents a case study of applying a Bayesian approach to forecast demand and subsequently determine the appropriate parameter S of an (S−1,S) inventory system for controlling spare parts of electronic equipment. First, the problem and the current policy are described. Then, the basic elements of the Bayesian approach are introduced and the procedure for calculating the appropriate parameter S is illustrated. We apply the Bayesian approach in an innovative way to specify the initial prior distributions of the failure rates of three types of circuit packs, using the initial estimates and the failure history of similar items. Based on these priors, we determine the distributions of demand for spare parts and finally we calculate the required stock levels for each type at several locations. According to the proposed method, a lower base stock than the one currently used is sufficient to achieve the desired service level.

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