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    Please use this identifier to cite or link to this item: http://ir.lib.ncut.edu.tw/handle/987654321/6200


    Title: Construction of a 3C Product Mold Manufacturing Process Predictive Optimization Model
    Authors: 林文燦
    Contributors: 工業工程與(工程)管理系
    Date: 2013-02
    Issue Date: 2017-09-30 13:12:55 (UTC+8)
    Abstract: Mold trials are critical in the mold development process; therefore, it is necessary to develop predictive models that can control processing results and solve problems in processing parameter optimization to ensure manufacturing efficiency and processing quality. Using the six sigma method, this research constructed an optimized 3C (Computer, Communication, and Consumer electronic) product mold manufacturing process predictive model, and conducted an empirical study on the largest electronic products foundry. The Taguchi parameter design method, the back propagation network (BPN) prediction method, and genetic algorithms (GAs) were used to establish an optimization search module. The surface quality was inferred by the network predictive model as a limiting condition for acquiring the maximized material removal rate in milling. The optimized milling processing parameters of the maximum fitness degree can be determined by GA. The findings can serve as a practical reference for quality improvements and decision planning.
    Relation: Materials and Manufacturing Processes
    Appears in Collections:[Development of Industrial Engineering and Management] 【工業工程與管理系所】期刊論文

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