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題名：建構塑膠射出成形智慧製造系統之研究
作者：阮孟雄
作者(外文)：Nguyen,Manh-Hung
校院名稱：中華大學
系所名稱：科技管理博士學位學程
指導教授：陳文欽
學位類別：博士
出版日期：2017
主題關鍵詞：塑膠射出成形；工業4.0；物聯網；巨量資料；雲端運算；智慧製造系統；田口方法；變異數分析；倒傳遞類神經網路；改良粒子群最佳化-基因演算法；PIM；industry 4.0；IoT；big data；cloud computing；IMS；Taguchi method；ANOVA；BPNN；modified PSO- GA
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隨著時代的進步與塑膠工業的迅速發展，塑膠射出成形應用的範圍也越來越廣泛，在許多電子、機械、航太、汽機車或一般生活用品等，該如何產出優良的產品，有效掌控品質良率與量產，是迫切需要改善的問題。近年來工業4.0、物聯網、巨量資料與雲端運算之推波助瀾下，產品不斷被要求輕、薄、短、小、多功能、精度佳、省能源，面對此艱鉅挑戰，建構具新一代射出成形智慧製造系統，扮演非常重要之角色。
本論文所提塑膠射出成形智慧製造系統包括智慧製程參數最佳化系統、參數資料庫管理系統，以及即時監控系統等三個子系統。首先智慧製程參數最佳化系統運用田口方法、變異數分析、多層感知器、倒傳遞類神經網路與改良粒子群最佳化-基因演算法建構最佳化模型，搜尋最佳製程參數組合；其次建構製程參數資料庫管理系統，此資料庫管理系統，儲存射出成形實驗數據、智慧製程參數最佳化系統產出之最佳參數組合、以及成形件產品編號與多品質目標值；最後建構射出成形即時監控系統，將建立射出成形圖形監控介面，監控範圍包含射出成形機台參數即時監控與多品質最佳化系統產出之最佳參數組合，並將最佳參數組合傳送並改變射出成形機台參數，並智能化監控產線機台狀況。本智慧製造系統具備即時監控、製程參數優化以及資料庫管理，可協助射出成形公司新產品開發，並有效提升產品的良率及製程穩定性，進而提升射出成形產業之全球市場競爭力。
Along with the progress of times and the plastic industry’s rapid development, plastic injection molding (PIM) has become one of the most important methods in plastic manufacturing with increasingly wider applications. Presently, PIM products are ubiquitous in a variety of applications like electronics, mechanics, aviation, aerospace, automobile, motorbike, and various general household items. With the booming development of PIM products, the requirements for these products have increased significantly. Therefore, how to produce products with excellent quality, effectively control product quality, and solve the problems related to yield rate and mass production have become urgent issues. In recent years, the great trends of industry 4.0, internet of things (IoT), big data analytics and cloud computing, the design and manufacture of PIM products have being demanded to fulfill the criteria of being light, thin, short, small, multi-function, high-precision, and energy-saving. To tackle this arduous challenge, effectively developing a novel PIM intelligent manufacturing system is now playing a crucial role.
The dissertation proposes an intelligent manufacturing system (IMS) composed of three subsystems: intelligent parameter optimization system of PIM process, database management system, and real-time monitoring and control system. Firstly the intelligent parameter optimization system employs Taguchi Method, ANOVA, MLP, BPNN and modified PSO-GA methodologies to search for the optimal parameter setting. Then the database management system is used to access the experimental data and PIM process parameter settings, which encompasses PIM product ID with quality targets. Finally, as for the PIM real-time monitoring and control system, the system will establish a graphic monitoring and control interface, whose monitoring scope includes intelligent real-time monitoring, the parameters of PIM machine, and the optimal process parameter settings. It will also transfer the optimal process parameter settings to PIM machines and simultaneously change their parameters. The proposed IMS system can help the PIM firms search for better parameter settings for new plastic products, and it also can facilitate the PIM firms to avoid product defects more easily, enhance the stability in the PIM process and build sustainable competitive advantage over their competitors in the world.
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