Grey prediction model for forecasting the planning material of equipment spare parts in Navy of Taiwan

The inventory management of maintenance spars parts plays an important role on their logistic policy. However, for the reasons of insufficient data or uncertaine demand of maintainance requirement that we have, the traditional forecasting method is generally hard to predict the optimal quantity of spare parts fitting the requirement. In this study we introduce Grey Prediction Model (GPM) to coping with such problem. After taking thrce types weapon system periodic items of planning material from 1999 to 2002, we then apply GM(1,1) model to predict the planning requirement of intermittent spare parts of 2003. In order to verify the perfomance of our forecasting model, we also compare the results with the observed data which are calculated by the rule of technical manual of equipments. Through this study, we demonstrate that the GM(I ,l) conduct a good accuracy on prediction of spare parts especially in situations of insufficient data, which accurate prediction should reduce the operation cost and improve the reliability of maintenance equipment.