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Spare parts planning is a complex task, involving a large number of SKUs (stock-keeping units) with intermittent demand patterns, making forecasting and inventory control very difficult. Intermittent SKUs often comprises 60 percent or more of total inventory in an industrial setting, thus an efficient selection of the best inventory methods implicates huge cost reductions and service level improvements. Due to the large amount of spare part SKUs held in companies, the inventory system cannot be configured manually on an individual basis. Therefore, some studies propose a sub-grouping of intermittent demand patterns by a categorization scheme. This approach entails two advantages; a categorization will provide the inventory manager with a better overview of the large number of SKUs to be dealt with, similar to the ABC-analysis by Dickie (1951) which still represents the most widely spread inventory tool used in practice. However, the main advantage of applying a categorizing scheme is to obtain sub-groups that have similar inventory management requirements. This comprises the opportunity to develop inventory rules for each sub-group and subsequently allow an automated configuration of the sub-groups’ single- echelon inventory systems. The goal of this chapter is to provide a comprehensible overview for practitioners and academics of recent results on intermittent demand categorization. For researchers the paper shall represent a base from which further research can be undertaken. For practitioners the paper shall comprise a guide on how to use current research results to incorporate an intermittent demand categorization scheme to exploit latest forecasting and inventory control methods in an efficient way. Categorization schemes have great potential to increase service level, to reduce inventory investment and to lower the need of manually adjustments due to an automated system. |
