| dc.description.abstract | In order to meet customers’ demand, every business needs to keep some inventory no matter what inventory management strategies operates. Companies constantly face the issue and potential risk of high inventory costs or high backlog cost including losing sales.
In this study, we deal with the raw material of Pump Shaft with unexpected delivery, which is about four to five months longer than customers’ given lead-time for following three main purposes.
First, to improve material management, material number conversion is based on the cutting points per customers’ required length. Utilizing pooling inventory method converts continuous material number into be discrete material number for differential customers’ service. Second, to improve forecasting method, evaluating the relationship between changes in Brent Oil Price, global rig counts and Pump Shaft demand in 2016 ~ 2018 and then modeling the forecasting liner regression. Third, at the same time, to mitigate the deviation of forecasting in case of occurring force majeure, building an inventory model in Arena seeks to give optimized order up to inventory position with targeting minimum costs using a heuristic optimization tool, OptQuest, take into account the discrete probability of demand arrives, and demand size and raw material delivery.
Therefore, the study’s aim was to organize the material master, construct the forecasting of Pump demand and get the optimal inventory position in the target of minimize inventory cost.
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