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研究生:賴宥呈
研究生(外文):Yu-ChenLai
論文名稱:智能製造執行系統之數據分析架構設計
論文名稱(外文):Data Analytics Framework for Smart Manufacturing Execution Systems
指導教授:陳裕民陳裕民引用關係陳宗義陳宗義引用關係
指導教授(外文):Yuh-Min ChenZong-Yi Chen
學位類別:碩士
校院名稱:國立成功大學
系所名稱:製造資訊與系統研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2018
畢業學年度:106
語文別:中文
論文頁數:58
中文關鍵詞:工業4.0數據科學製造執行系統智能化
外文關鍵詞:Industry 4.0Data ScienceMESSmart
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製造執行系統(Manufacturing Execution System, MES)為製造的應用系統之一,能將即時的生產資訊和其他資訊系統(如企業資源規劃、生產規劃與排程系統等)整合,使得營業、工廠或流程控制系統得以連結,以提高企業營運與生產績效。此外,MES系統也收集製程中人、機、料、法、環以及生產相關之資料,進行生產績效影響因子或重要管制點監控,以確保生產之效率與產品品質。

大數據之產生、資訊科技之進步與運算能力之提高,使人工智能(Artificial Intelligence, AI)再度興起,並成功地應用在許多領域,也使產業進入「工業4.0」時代。在工業4.0環境下,資料科學(Data Science)之方法與技術被廣泛應用,冀從「資料」萃取出「有價值之資訊」以改善決策,MES系統也必須進步為Smart-MES來適應智能生產的需求。

本研究針對工業4.0智能化生產之需求,運用Data Science之方法與人工智慧技術,規劃與設計Smart MES模式與資料分析架構,並開發其生產績效影響因子分析技術以及生產績效預測技術。本研究成果將有助生產智能化之實現,進而提昇產業競爭力。
Manufacturing Execution System (MES) is one of the manufacturing systems that integrates real-time production information with other information systems (such as production planning and scheduling systems) to make business, plant or process control systems to be linked, and improve business operations and production performance. In addition, the MES system collects data from people, machines, materials, processes, environmental, and production-related data from the manufacturing process to monitor impact factors on production performance or critical control points for guaranteeing efficiency and quality of production.

The emergence of big data, the advancement of information technology and the improvement of computing power have led to the re-emergence of artificial intelligence (AI) and its successful application in many fields, and the industry has entered the era of Industry 4.0. In the industry 4.0 environment, Data Science's methods and technologies are widely used. From the data to extract valuable information to improve decision-making, MES systems must also evolve into Smart-MES to adapt to intelligent production. Demand.

This study focuses on the requirement of industrial 4.0 intelligent production, using Data Science's method and artificial intelligence technology, planning and designing Smart MES model and data analysis architecture, and developing its analysis technology of impact factors on production performance and forecasting technology of production. The results of this study will help to realize intelligent production, and thus enhance the competitiveness of the industry.
摘要 I
目次 VIII
圖目錄 X
表目錄 XI
第一章 緒論 1
1.1 研究背景 1
1.2 研究動機 2
1.3 研究目的 2
1.4 研究項目 3
1.5 研究步驟 4
第二章 文獻探討 6
2.1 應用領域 6
2.1.1數據科學(Data Science) 6
2.1.2智能製造(Smart Manufacturing) 7
2.1.3製造執行系統(Manufacturing Execution System, MES) 8
2.1.4虛實整合系統(Cyber Physical System, CPS) 9
2.1.5智能化(Smart) 10
2.2 應用技術與方法 11
2.2.1關聯規則分析(Association Rule Analysis) 11
2.2.2類神經網路(Artificial Neural Networks, NNS) 12
2.3 相關研究 13
第三章 智能製造系統模式設計 15
3.1 製造系統 15
3.1.1 PDCA為基之生產循環架構 15
3.1.2製造系統元素 17
3.1.3製造系統資料模型 18
3.2 智能製造執行系統 20
3.2.1 製造執行系統 20
3.2.2 智能製造執行系統架構 22
第四章 分析模式與方法設計 26
4.1 分析模式 26
4.1.1 分析程序 26
4.1.2 因子與趨勢分析 28
4.2分析方法 30
4.2.1生產績效影響因子分析 30
4.2.2生產績效影響因子監控 35
第五章 機制實作與驗證 38
5.1 生產製造資料 38
5.1.1分析軟體工具使用 38
5.1.2 分析資料模型 38
5.1.3生產製造資料表 41
5.2 實作與驗證 44
5.2.1生產績效影響因子分析實作 44
5.2.2生產趨勢預測分析實作與預測驗證 47
第六章 結論與未來方向 53
6.1 總結 53
6.1.1 未來研究方向 54
參考文獻 55
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