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Using DOE technology to Improve the Expert System for the Injection Molding

Replacing steel and wood with plastic is the developing trend in the modern industry. In many shaping processing methods¡M the injection molding technology is widely used in plastic industry for its good adaptability¡M high producing efficiency and easy-achieve to automation. Injection molding is a very complicated physical process¡M the molding parameters (including temperature¡M pressure¡M time¡M speed and position etc) and environment condition will directly affect the flowing condition of melting plastic and final quality of products¡M so to obtain the best molding parameters is the key to improve the quality of the plastic products.
The traditional method of adjusting parameters is try and error¡M which wastes time and materials. And it¡¦s also hard to accumulate and transmit experience¡M so we urgently need to find a new method. By going through a long time of experiment and exploring¡M we found that the DOE (Design of Experiment)¡M which is one of the most important tools of 6 sigma¡M can be applied to improving the molding processing¡M and it will bring us the innovation of injection molding technology. DOE is one of the mathematic methods¡Mwhich bases on Probability theory¡M Statistics and Linear algebra¡M through rationally arrange experiment and correctly analyze the results of experiment¡M to obtain the best parameters. In the processing of exploring¡M we have obtained first-step success in shortening cycles¡M reducing weight of product and improving qualities. For the sake of extending and developing the methods of DOE applied to molding technology in the company and transmitting experience of experts¡M we are going to conclude many DOE cases as a rule¡M establish a database¡M develop an injection molding expert system¡M which will be the effective way to bring cost down¡M improve efficiency and establish a core-competition capability of injection molding technology.

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0812108-160604
Date12 August 2008
CreatorsTsao, Cheng-lin
Contributorsnone, none, none
PublisherNSYSU
Source SetsNSYSU Electronic Thesis and Dissertation Archive
LanguageCholon
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0812108-160604
Rightsnot_available, Copyright information available at source archive

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