Research on classification method of spare parts inventory based on warranty data

In this paper, we analyze the warranty data in after sales service, considering the reliability characteristic parameters of spare parts in use (MTBF), supply characteristics (replenishment lead time and supplier scarcity), part cost and part criticality. This paper constructs a multi-criteria classification model for ABC classification of spare parts by using intelligent machine classification approaches - support vector machine (SVM). The main contribution of this study is the interaction between warranty data and the multi-criteria SVM-ABC classification method. A case study is presented to illustrate the model. The test results show the good performance of this model.