Most inventory models are based on assumptions that demand follows a certain theoretical distribution (such as Normal or Poisson distribution). For items with relatively fast moving, such an assumption may hold true. However, for slow moving items such as spare parts, we rarely found that demand follows such theoretical distribution. Consequently, using standard inventory control models to set inventory parameters for spare parts would result in either low service level, high inventory level, or both. In this study we use Monte Carlo simulation to determine inventory control parameters for spare parts. We employ a well known periodic review base-stock inventory control models where the replenishment decisions are governed by maximum and minimum inventory levels. The initial solutions were generated using standard inventory control models. Monte Carlo Simulation is then used to evaluate the parameters against other neighboring values in terms of inventory cost and service level. We apply the procedure for cabin spare parts in an aircraft maintenance facility.
This research has been published on APIEMS (Asia Pacific Industrial Engineering and Management Society) 2010.
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