Forecasting spare parts demand based on degradation modeling

Proactive maintenance and spare parts ordering are two fundamental components for prognostics and health management of equipment. To achieve timely proactive maintenance and spare parts ordering, it is necessary to forecast the demand of spare parts accurately according to the equipment´s operating state. To do so, a degradation modeling based method is proposed to forecast the demand of spare parts. Specifically, equipment´s lifetime is predicted in a probability form by modeling its degradation process. Based on the lifetime distribution, the demand distribution of spare parts in a future time span can be forecasted by evaluating the convolution of the lifetime distribution. Finally, a case study for gyro´s data is provided to illustrate the implementation of the proposed method.