Proactive Planning and Analysis for Dynamic Events in Supply Chains

• Main Authors: Chun-Wei Chen, 陳俊維
• Other Authors: 周雍強
• Format: Others
• Language: zh-TW
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/11248988906032158781

碩士 === 國立臺灣大學 === 工業工程學研究所 === 94 === High level of uncertainties in product demand and manufacturing is a major characteristic facing many manufacturing supply chains. If a supply chain is lean in buffer capacity or inventory, an event that arises from the uncertainties will have an impact not only on the operation of the plant in which the event takes place but also on other plants of the chain. In semiconductor manufacturing there are also many internal or external uncertainties and capacity is lean due to the extremely high cost of equipment. When dynamic events occur, they will have a serious impact on the whole chain. Based on their impact on the nominal operation, uncertainties can be distinguished in three levels: deviation, disruption and disaster. Supply chains are usually designed to cope with deviation in operation parameters and they undergo irreversible changes when disasters strike. The focus of this paper is on the behavior of supply chains under disrupting events in full-load states. To manage dynamic events, a supply chain operation model is described which comprises a production function for production units under full-load and a dynamic model linking the operation of multiple units over a certain duration. In the literature, there are two approaches to modeling the behavior of production units which are time-delay function and input-output control. The production functions in the literature are for regular load scenarios, so a full-load production is derived by using of flexible capacity through alternative routing machines. Finally, a mathematical solution method based on non-linear programming is described for optimizing a recovery path. This method enables supply chains to treat disrupting events as controllable deviation event and to enhance the controllability of the chain.