2020 : Joint Optimization Model of Spare Parts Inventory and Planned Maintenance under Uncertain Failures
Nurhadi Siswanto S.T., MSIE.,Ph.D
Spare parts are often considered as Class C items, because of their low cost and low demand among the stocked items, but the availability of spare parts is important to support maintenance requirements. Optimizing inventory parameters is the main problem of spare parts management in order to maintain a small number of SKUs kept in a store, and optimization techniques are commonly used to balance inventory cost and spare parts availability. Thus, this research proposes a joint optimization model of single-item multi-period spare parts inventory management and planned maintenance under uncertain failures. First, we present an Mixed Integer Nonlinear Programming (MINLP) formulation of the inventory optimization model under (s, S) policy with T periods of the order interval. Second, we combine this formulation with the predictive maintenance interval, representing the uncertain failures under predefined distribution. Since the model is nonlinear and stochastic, it is difficult to use exact methods to tackle this problem. Therefore, we combine the previously introduced MINLP formulation with a metaheuristic approach to solve the problem. Lastly, we perform a computational study to demonstrate the effectiveness and efficiency of the proposed approach. The output of this research are a publication of one Scopus indexed international journal paper with the minimum category in Q2 and one completed thesis book.