A Simulation Evaluation of Multi-site Order Allocation and Exchange Procedures

• Main Authors: Shang-Ming Fu, 傅上茗
• Other Authors: Shin-Ming Guo
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/76493141628758104878

碩士 === 國立高雄第一科技大學 === 運籌管理研究所 === 102 === 　　More and more enterprises have expanded their production systems. They consider either cost or market factors and relocate their plants abroad. Those relocation areas include mainland China, Southeast Asia, Europe, and America and format a multi-site production network. 　　It is necessary to develop a multi-site order allocation model in such an environment. One can consider the capacity burden of each plant and the production cost difference, and then makes the appropriate allocation to reduce production costs, while maintaining good order delivery performance. 　　This research develops a multi-product, multi-site order allocation model. Based on ratios of remaining ATP allocation, dedicated equipment requirements, production costs, and production flexibility, it carries out the order allocation using a batch process. It also establishes a mechanism to exchange orders among plants in order to provide better due dates to serve customers. 　　In this study, we use a set of multi-site orders data from the literature to simulate and analyze the Arena programs to compare different order allocation models. Experimental results show that using ratios of remaining ATP allocation could make the utilization of each plant more balanced. Batch allocation could decrease the effect of emergency orders on system burden. The order exchange mechanism could rearrange the originally rejected orders and provide better due date. Thus serve more customers. 　　This research also analyzes the effects of market demand increases, shorter delivery time expected by customers, and the change of product demand mix. The result shows that our multi-site order allocation model can significantly improve the amount of accepted orders and delivery performance. It improves overall profitability.