Fuzzy Available-to-promise modeling of Make-To-Ordermanufacturing with material supply uncertainty

• Main Authors: Chun-Nan Lin, 林濬南
• Other Authors: Kune-Muh Tsai
• Format: Others
• Language: zh-TW
• Online Access: http://ndltd.ncl.edu.tw/handle/14363958250596467991

碩士 === 國立高雄第一科技大學 === 運籌管理所 === 94 === High-tech industries have played a significant role in Taiwan’s economy. As the competition becomes even more intense than before, manufacturers are facing strict customer service requirements on due date promising and shorter lead time. Available-to-promise (ATP) can help manufacturers respond quickly requests from customers, and assist manufacturers in assuring on time delivery. However, in implementing ATP, many uncertain factors could jeopardize the quality of promised delivery time and quantity to customers. For example, uncertain material supply could result in either high inventory level or holding up of production. Few research stated the issue of uncertain part supply affecting outcomes from ATP systems. We implemented fuzzy modeling to tackle uncertain part supply, and modeled the proposed fuzzy-ATP as a rolling fuzzy programming problem to maximize profits of manufacturers with capacity and material constraints under multi-site and Make-To-Order (MTO) TFT-LCD industry environment. The fuzzy-ATP mechanism includes mainly two stages: the first is to optimize customer orders allocated to multi-site plants, and the second is to re-allocate orders that cannot be allocated in the first stage by searching among all plants with available capacity and material to meet customer due dates. Results found that for manufacturers, fuzzy-ATP can reduce the chance of undelivered promised customer orders when actual material supply is below estimated material supply that the manufacturers can evaluate their own chance of risk in promising customer orders. Besides, manufacturers can provide customers with a fuzzy delivery date based on fuzzy material supply, which can help customers in devising their delivery plans to markets.