Simulation-based approaches in solving multiple products and outsourcing contractors order allocation problem – an IC design house case

碩士 === 國立成功大學 === 製造工程研究所碩博士班 === 94 === Order allocation is always a very important decision problem when firms have insufficient capacity or technique to produce their own designed product completely. Firms have to select the most applicable outsourcing company to execute the production and then s...

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Bibliographic Details
Main Authors: Cheng-Ching Li, 李鉦慶
Other Authors: Ta-ho Yang
Format: Others
Language:zh-TW
Published: 2006
Online Access:http://ndltd.ncl.edu.tw/handle/55680134606996127213
Description
Summary:碩士 === 國立成功大學 === 製造工程研究所碩博士班 === 94 === Order allocation is always a very important decision problem when firms have insufficient capacity or technique to produce their own designed product completely. Firms have to select the most applicable outsourcing company to execute the production and then satisfy their final customers. Therefore, the decision of outsourcing company selection will not only influence the company objective but also satisfaction of customer. A case study of IC design house was proposed. When an IC has been designed, the mask manufacturing will be outsourced firstly, then IC manufacturing, IC packaging, IC testing and final product taping. In this case, the order allocation problem only focuses on IC packaging, IC testing and final product taping process. Beside, think about total cost, yield and delivery rate are objectives. Use Simple additive weighting method let three objectives to a total objective. There are five outsourcing companies can choose and every outsourcing company have different process cost, yield and transport time. In order to close to real case, we think about amount discount、transport batch and delay cost. Besides, the research uses the characteristic of mixture design which the sum of variables is one. Making every outsourcing company's part is a variable. And use simulation tool to model the IC design house order allocation process. Through the simulation model, we can have different plan's data to get response surface. Then use mathematical programming and local search to get the best order allocation result.