The development of a demand forecasting web application for Spare Parts Management \\ using Bootstrapping Method

Abstract

The forecast has been recognized as one of the most essential parts of spare part management, which often impacts inventory costs and performance to a large degree. In the case study, the demand pattern of spare parts from a subsea maintenance service provider is characterized as intermittent demand. This demand pattern is common among spare parts which accounts for a large portion of inventory costs. As a means of predicting its intermittent demand, there is a method called WSS bootstrapping method, described in the literature. We developed a web application based on the WSS bootstrapping model by Willemain et al. (2004) and an adapted jittering method by Rego and Mesqutia (2015). The computational results show that the results of the bootstrapping model often contain true value when using the 99\% confidence interval. The error of the model is lower than our analysis criterion. Therefore, the performance of the bootstrapping model is satisfying.