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. Finally, we present the results of applying the Bayesian approach in an innovative way to determine the stock levels of three types of circuit packs 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.inventory control;spare parts;case study;Bayesian analysis

Evolutionary multiobjective optimization of the multi-location transshipment problem

We consider a multi-location inventory system where inventory choices at each location are centrally coordinated. Lateral transshipments are allowed as recourse actions within the same echelon in the inventory system to reduce costs and improve service level. However, this transshipment process usually causes undesirable lead times. In this paper, we propose a multiobjective model of the multi-location transshipment problem which addresses optimizing three conflicting objectives: (1) minimizing the aggregate expected cost, (2) maximizing the expected fill rate, and (3) minimizing the expected transshipment lead times. We apply an evolutionary multiobjective optimization approach using the strength Pareto evolutionary algorithm (SPEA2), to approximate the optimal Pareto front. Simulation with a wide choice of model parameters shows the different trades-off between the conflicting objectives

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. Finally, we present the results of applying the Bayesian approach in an innovative way to determine the stock levels of three types of circuit packs 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

Optimal inspection policy for three-state systems monitored by variable sample size control charts

This paper presents the expected long-run cost per unit time for a system monitored by an adaptive control chart with variable sample sizes: if the control chart signals that the system is out of control, the sampling which follows will be conducted with a larger sample size. The system is supposed to have three states: in-control, out-of-control, and failed. Two levels of repair are applied to maintain the system. A minor repair will be conducted if an assignable cause is confirmed by an inspection, and a major repair will be performed if the system fails. Both the minor and major repairs are assumed to be perfect. We derive the expected long-run cost per unit time, which can be used to obtain the optimal inspection policy. Numerical examples are conducted to validate the derived cost