Many studies describe challenges facing large manufacturers who must efficiently control an inventory of tens of thousands of finished products, maintenance and replacement or spare parts (Ward 1978; Gelders and Van Looy 1978; Dunsmuir and Snyder 1989; Hua et al. 2007). Wagner and Lindemann (2008) have urgently called for future research on strategic spare parts management. When stocking spare parts, a few parts often represent the bulk of the investment and the majority of the demand. However, it is important to be able to forecast the demand rate for the slow-moving items as well as the heavily used parts. If a product has not had a demand over a specified duration of time, its demand would be projected to be zero based on many of the popular forecasting models, such as simple exponential smoothing or moving averages. Yet, this product may still be required and be worth carrying, particularly if the inventory cost is well managed.
Unbiased Estimator Prediction Interval Spare Part Software Reliability Demand Rate
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