Economic Order Quantity Determination for Raw Material Color Category : A Case Study of Automotive Parts Industry

Abstract

This research aims to analyze the forecasting techniques and analyze the appropriate order quantities to enhance efficiency in color category raw materials inventory management. It starts by grouping raw materials using the ABC Analysis principle, focusing on Group A, which has the highest annual order value. There are seven types of raw materials in Group A, with a total value of 8,504,130 baht, accounting for 78.06% of the total value of all color category raw materials. Next, the data is used to forecast future product demand using a forecasting software program. Four forecasting methods are used: Simple Moving Average, Single Exponential Smoothing, Double Exponential Smoothing, and Winter’s exponential smoothing method. The forecast values obtained from the forecasting methods with the lowest forecast errors (MAPE, MAD, MSD) are then analyzed Variability Coefficient before being used to calculate the appropriate order quantities. The Variability Coefficient (VC) should not exceed 0.25. Among the color category raw materials, four types meet the criteria for suitable analysis of economic order quantity: NH-303M, NH-B99M, R-366, and NH-B61P. According to the study results, the improvement of the purchasing format for all four types of color category raw materials can be achieved as follows: NH-303M's overall cost per year decreased by 9.22%, NH-B99M's overall cost per year decreased by 1.65%, R-366's overall cost per year decreased by 16.59%, and NH-B61P's overall cost per year decreased by 43.38%. After adjusting the purchasing format for the four types of color raw materials, it was found that the overall cost could be reduced by 15,819 baht per year, which is approximately 13% per year.