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The Optimal Configuration Of Flexible Manufacturing System Based On Adaptable Genetic Algorithms

Posted on:2008-01-17Degree:MasterType:Thesis
Country:ChinaCandidate:Q WangFull Text:PDF
GTID:2132360212974306Subject:Mechanical Manufacturing and Automation
Abstract/Summary:PDF Full Text Request
With the development of the Information Technology and the Computer Networks, the global character of the World Economy becomes more and more obvious. It makes the Manufacturing as the national stanchion be faced with the situation that the competition of the global Market, resource, technology and personnel is getting furious, and the command of the customization, high quality and quick consignment is more and more. Because all of these, the Manufacturing Automation is playing a very important role in modern production increasingly.The Manufacturing System is the substantial circumstance for the realizing production process and the necessary physical condition. The Flexible Manufacturing System can be used in the production which has kinds of varieties and small batch size. It offers a powerful support for realizing agility of manufacturing in the 21st century. But it has complicated composing, long constructing term and high investment, so optimal configuration is very important. The plan of optimal configuration not only determines the system's construction and investment, but also affects the system's running capability. Once it has been accomplished, it will influence the production activities all the time in the future.Because of the importance of the optimal configuration of Flexible Manufacturing System, some experts in this field did some research about its theory and application. But this problem has the character that is many parameters, complex coupling, multi-objectives, nonlinearity etc., so this work is extremely difficult.Applying the theory and technology in multi-subject integratively, this dissertation establishes the Closed Queueing Networks for the optimal configuration of the Flexible Manufacturing System. However, this model is nonlinearity and has mixed discrete variables, and can't be solved by normal algorithm. Therefore, Adaptable Genetic Algorithms is used with the help of computer, which can ensure the accuracy of the solution and improve the efficiency. A visible interface is developed for the convenient using in project.Based on the foregoing content, an example of this problem circumstantiates the solving process. At last, the whole-length research is summarized and the writer picks up with her opinions and suggestions for the further work.
Keywords/Search Tags:Flexible Manufacturing System, Closed Queueing Networks, Adaptable Genetic Algorithms, Implicit Enumeration
PDF Full Text Request
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