An analysis of inventory classification for service parts.

After-sales service is a core business to the corporations manufacturing durable goods, not only lots of profit could be gained but accumulating customers’ information by providing solid service to customers. One key factor in providing good service is an efficient service parts management, and one key decision in service parts management, like all kinds of inventory management, is deciding an appropriate safety stock level (service level) for each spare part. Previous studies on safety stock level usually focus on one single item, while taking inventory cost and shortage cost into consideration. They suggested the optimal level should achieve its minimum total cost. Unfortunately, it is impractical to deal with only one item, and most of time, the shortage cost is just too difficult to assess accurately. To a provider of after-sales service, a desired problem is how to set all parts’ service level so that the average service level would reach its maximum. In order to solve the optimal service level for each part, this thesis constructs a mathematic model based on the problem, taking parts’ demand characteristics, inventory cost and criticality into account. By examining the numerical examples and deriving the KKT conditions, we are able to searching patterns of optimal service levels. Once we confirm the patterns, we could use it as some kind of criteria to classify all service parts into three categories: “High service level”, “Moderate service level” and “Low service level”, then by giving these categories respective service level, it is an effective way of setting service levels. As the result shows, the one with high criticality, low cost and demand variability should be classified into category “High service level” and set at high service level.