A Study on the Application of Genetic Algorithm to GaAs Semiconductor’s Backside Processing for Scheduling Research
碩士 === 元智大學 === 工業工程與管理學系 === 93 === Owing to the vigorous competition and the fast changing market environment, nowadays, the manufacturers have to shorten the cycle time and minimize the total completion time of the products in order to lessen the pressure of the inventory. Therefore, to provide a...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2005
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| Online Access: | http://ndltd.ncl.edu.tw/handle/88276235860725705484 |
| Summary: | 碩士 === 元智大學 === 工業工程與管理學系 === 93 === Owing to the vigorous competition and the fast changing market environment, nowadays, the manufacturers have to shorten the cycle time and minimize the total completion time of the products in order to lessen the pressure of the inventory. Therefore, to provide an effective production schedule for the shop floor manager is very important other than reduce the production costs.
This research deals with the production scheduling problem in the manufacturing process of the GaAs Semiconductor’s Backside Processing. After turning three single machine processes in the factory (a flowshop) of the stages of the gallium semi-conductor, the complexity and scale of the problem increase therefore a GA based scheduling approach is proposed and developed to provide a practical solution approach for the company.
The major direction of the research is mainly to solve the problem efficiently within a limited time frame therefore GAs is choosed as an implementation tool. To compare with other approaches, traditional heuristic rules are applied to solve the problem at hand. First Come First Serve and Shortest Processing Time rules are applied in these experimental data. According to the experimental resulte, the developed GA approach can improve around 8% in terms of solution quality with a little cost of computational times.
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