Forecasting Model for Advanced Purchasing Planning by Exponential Smoothing

Authors

  • จารุเดช โตจำศิลป์ ภาควิชาวิศวกรรมอุตสาหการ คณะวิศวกรรมศาสตร์ สถาบันเทคโนโลยีพระจอมเกล้าเจ้าคุณทหารลาดกระบัง
  • สิทธิพร พิมพ์สกุล ภาควิชาวิศวกรรมอุตสาหการ คณะวิศวกรรมศาสตร์ สถาบันเทคโนโลยีพระจอมเกล้าเจ้าคุณทหารลาดกระบัง

Keywords:

Exponential Smoothing, Reliability Index, Forecast Accuracy Rate

Abstract

This research is to study and find the time series forecasting model in order to forecast tyre demand of a case study warehouse. The data is gathered weekly from January 2015 to March 2018 with the total of 168 weeks that is used and separated into 2 groups. The first group contains 156 weeks from January 2015 to December 2017 for forecasting. The second group contains 12 weeks from January 2018 to March 2018 for comparing and finding the most suitable model. This research uses 4 techniques which include 1) Brown’s One Parameter Linear Exponential Smoothing, 2) Holt’s Two Parameter Linear Exponential Smoothing, 3) Additive Seasonality Method, and 4) Winters’ Linear and Seasonal Exponential Smoothing. The suitable forecasting models are chosen by considering the percentage average forecast accuracy of advanced sum forecast period as 3, 6, 9 and 12 weeks and are compared with sum actual demand according to those periods. The result of this research shows the best forecasting models for all 11 tyre models for inventory requirement planning.

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vol35no2

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Published

2018-06-29

How to Cite

[1]
โตจำศิลป์ จ. and พิมพ์สกุล ส., “Forecasting Model for Advanced Purchasing Planning by Exponential Smoothing”, Eng. & Technol. Horiz., vol. 35, no. 2, pp. 22–32, Jun. 2018.

Issue

Vol. 35 No. 2 (2018): April - June

Section

Research Articles

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