Forecasting service parts demand for a discontinued product

Stochastic demand forecasting methods for service parts of a discontinued product are proposed. The identified four major factors are the number of product sales, the discard rate of the product, the failure rate of the service part, and the replacement probability of the failed part. During a given period, typically a year, the number of failed service parts is estimated using the first three factors, and then the demand for those service parts is obtained with the use of the last factor. A stochastic model is derived to estimate the demand in a certain prediction interval, and the closed-form solutions in the case of a constant failure rate are provided. An approximate model is proposed to render actual computation possible when the part failure time is not distributed exponentially. Numerical data from the automotive industry are used to validate the model.