Demand analysis and forecast for spare parts of perishable hi-tech products

As is known to all, the life cycle of perishable hi-tech products(PHTP) is so short, and the update rate is so fast that market demand of older products is influenced, changed dynamically continuously. Generally, when the product goes wrong and better products continuously appear, customers will replace the failure components, but more and more of them tend to buy updated products now as time goes by, which influences the spare parts demand and brings more difficulties to forecast the demand. Under this background, we established a Spare Parts Forecasting Model Based on the Installed Base Information (IBI-SPFM) in this paper, which considered the influence of customer behavior on spare parts demand. Moreover, it can be showed that our IBI-SPFM not only can work out a better forecasting value, but can provide us the installed base of products and build-in components with different age categories both by theoretical analysis and numerical case. Our method is of much significance when companies are confronted with relative decision-making problems.