Forecasting and purchasing planning for shelf life-limited spare parts

Abstract

Forecasting and Purchasing Planning for Shelf Life- Limited Spare Parts with a case study of company, purchasing spare parts from factories by selecting a forecasting method and applying a mathematical model. The purposes of this research are to improve the inventory quantity to be suitable for customers' demand, to reduce holding cost and to minimize the total inventory cost. In the past, the company operations didn't have purchasing planning strategy in the case study, the purchasing would be ordered when the inventory level is 0 that result shortage spare parts sometimes and the company had the policy about the spare parts with a limited 5-years lifetime. We propose a new strategy about applying a mathematical model for purchasing planning spare parts that minimize the total inventory cost by using a new safety stock (SS) and customers' demand that is the most accurate forecasting method with the lowest Mean Absolute Deviation (MAD) from 5 forecasting methods: 1) Moving Average, 2) Single Exponential Smoothing, 3) Double Exponential Smoothing, 4) Holt-Winters Smoothing, 5) Monte Carlo Simulation. Finally, the results of this study were found that the mathematical model for purchasing planning spare parts can prevent the inventory shortage problem, to reduce the quantity of expired spare parts and minimize the total inventory cost from the current purchases by 19.08%.