Sales forecasting and material placement optimization: A case study of Taiplas Recycle Co., Ltd.

Abstract

The objectives of this study were as follows: 1) To select a sales forecasting method to determine the production plan. 2) To study strategies for managing raw material storage to increase efficiency. 3) To reduce the time to find raw materials. 4) To reduce the amount of damaged raw materials.  The sample group used in this research consisted of the following plastic types: black PP pellets, white PP pellets, masterbatch white pellets, black PP regrind, white PP regrind, and masterbatch white regrind. These materials were chosen because they are the highest-selling plastics.

The study found that the most suitable forecasting model is Moving average method because it is the method with the lowest error. To find a method to forecast the appropriate number of raw materials in order to plan the allocation of raw material placement areas and improve the process of disbursing raw materials according to the FIFO model together with the ECRS concept using the principle of simplification to consider the inefficiently steps, the distance before the renovation was 1,270 meters, and after the renovation, the distance was 410 meters, causing the distance to be reduced by 860 meters, or equivalent to 32.28%, and causing the time to decrease by 21 minutes, or equivalent to 5.02%, and It was found that after improving the raw material storage layout, Originally there were 64,389 kilograms of damaged raw materials. After improvements, there was no such amount of damaged raw materials.