Forecasting and Purchasing Planning for Shelf Life-Limited Instruments Equipment Spare Parts

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Sasithorn Kitti-udomporn
Suwitchaporn Witchakul

Abstract

         Forecasting and Purchasing Planning for Shelf Life-Limited Instruments Equipment 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. There were 17 items or 80% of total expired spare parts value that would be taken for forecasting and purchasing planning in this case study. 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. From experiments, 17 items of the spare parts were the most suitable with Moving Average, Single Exponential Smoothing and Double Exponential Smoothing Method. In addition, this study calculated the new safety stock level at 95% confident level for new purchasing planning next year. Finally, The results of this study were found that the mathematical model for purchasing planning spare parts, could prevent the inventory shortage, reduce holding cost and minimize the total inventory cost from the current purchases of all items by 8,384,223 baht or decrease the average cost of 493,189.59 baht/year that is 17.55%

Article Details

Section
Research Article

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