The implementation of Material Flow Cost Accounting analysis to determine the optimal sample size and lot size in serial multi-stage processes

Abstract

© IEOM Society International. Product quality is a crucial factor that significantly affects customer's satisfaction and many organizations emphasize and invest large amounts in designing and assuring quality system to prevent flow of defectives along the process. Surviving in competitive environment many organizations attempt to reorganize their inspection policies in order to satisfy customer's expectations while reducing costs. Inefficient inspection policy can lead to significant wastage of resources. Therefore, the researches on designing efficient inspection strategy have been studied extensively in last few decades. This research applied the Material Flow Cost Accounting (MFCA) technique first to trace material and energy used both in terms of physical quantity and monetary units in order to analyze efficiency of process and then to design the lot size and quality inspection system that maximize ratio of total positive product cost to the total cost obtained from the MFCA concept. In this paper, an artificial bee colony (ABC) algorithm is used as a search algorithm for the optimal inspection sampling size and the lot size under serial multi-stage processes. This studied shows that the best solution obtained from the proposed methodology results in the production and inspection system with higher resource efficiency and greater proportion of the total positive cost.