基因演算法應用於面板產業Cell製程後段排程之研究—以H公司為例

郭建男

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基因演算法應用於面板產業Cell製程後段排程之研究—以H公司為例

Applying Genetic Algorithm for scheduling back-end process of cell production - Taking H company as Example

郭建男 , Masters　　Advisor：吳植森;利德江　　

繁體中文

排程演算法；基因演算法； TFT-LCD ODF機台； TFT LCD Cell process ； Scheduling ； Genetic Algorithm

Abstract │ Reference (33) │ Times Cited (4) │ Altmetrics

Abstract 〈TOP〉

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The complexities of scheduling and the diversities of manufacturing system make scheduling become a tough problem. Owing to the application of mathematics makes optimal scheduling become a NP-Hard problem and those assumptions simplified the complexities in shop floor. This research is trying to use Genetics Algorithm to solve the scheduling problem.
  This research is trying to study the scheduling problem under unrelated parallel machine manufacturing system. This kind of scheduling is known for its highly complex optimal combination problem in scholar field. Except for a few special cases, most of the problems belong to NP-complete problem. Those problems are encountered in manufacturing industries such as textile, printed circuit board, wafer test and BOPP-film industry. According to the panel industry in this study, its characteristics including: highly customer made, numerous order specifications, order changes are often, scheduling need flexibility, minimum stocks. Besides that, delivery stability is still a key factor that customer consider whether to order or not. Previous studies related to unrelated parallel machine scheduling problem mainly focus on total flow time or total tardiness as single performance indicator, However, under contemporary manufactory complex circumstances, single indicators can’t meet the need from decider, Taking this case as an example, H company only owns a Gen 5 factory, total tardiness is important indeed, but seeking a maximum capacity is also a critical issue (ie. minimum changeover), so this research is trying to satisfy both total tardiness and minimum change over as indicators.
  This research demonstrates Genetic Algorithm used in the cases can obtain schedules in short time with similar performance as compared to that of manual schedules.

Reference ( 33 ) 〈TOP〉

[2] 葉麗芬，雙目標非等效平行機台排程問題之探討，元智大學工業工程系，碩士論文，2001.
連結：
[4] 李勝隆，基因演算法於印刷電路板鑽孔排程之應用，元智大學工業工程系，碩士論文，2001.
連結：
[5] 蕭陳鴻，基因演算法於非等效平行機台排程之應用，元智大學工業工程系，碩士論文，2001.
連結：
[6] 莊文化，應用基因演算法於彈性流線型之工廠排程問題，國立成功大學，碩士論文，2004.
連結：
[7] 劉俊暉，應用基因演算法建立機台維修保養之研究，國立成功大學，碩士論文，2004.
連結：

Times Cited (4) 〈TOP〉

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