研究生: |
林沅霆 Lin,Yuan-Ting |
---|---|
論文名稱: |
臺灣智慧製造創新應用之研究-以AHP及DEMATEL方法分析 A Study on Taiwan's Smart Manufacturing Innovation Applications:Using of AHP and DEMATEL Methods |
指導教授: |
蘇友珊
Su, Yu-Shan |
學位類別: |
碩士 Master |
系所名稱: |
工業教育學系 Department of Industrial Education |
論文出版年: | 2020 |
畢業學年度: | 108 |
語文別: | 中文 |
論文頁數: | 108 |
中文關鍵詞: | 智慧製造 、層級分析法 、決策實驗分析法 |
英文關鍵詞: | Smart manufacturing, AHP, DEMATEL |
DOI URL: | http://doi.org/10.6345/NTNU202000393 |
論文種類: | 學術論文 |
相關次數: | 點閱:279 下載:0 |
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近年來,智慧製造受到了學術界和工業界的越來越多的關注,因為它為製造公司提供了競爭優勢,使生產變得更加高效率和可持續性。本研究分析相關智慧製造相關之文獻,歸納出智慧製造五個構面以及二十九項準則,五個智慧製造的構面分別為智慧設計、智慧生產、智慧工廠、智慧服務和工業物聯網管理。
本研究運用層級分析法(AHP)結合決策實驗室分析法(DEMATEL),兩種研究方法評估智慧製造構面與準則之間的權重與因果關係,藉由兩者結論判斷台灣優先發展智慧製造之策略。研究結果顯示五大構面中優先發展的是工業物聯網管理。而準則方面分別是:一、工業物聯網管理構面下硬體優先發展感測器、軟體著重於權限管理。而軟、硬體結合後再來做設備管理和建立標準通訊協議。二、智慧生產構面下優先發展先進製程控制,在機器學習最佳的製程之後達到機台智慧化。三、智慧工廠構面下優先發展數位轉型,再依據數位轉型的內容更新或是增加IT基礎設施。研究結果將提供台灣邁向智慧製造一個未來發展規劃。
In recent years, smart manufacturing has received more and more attention from academia and industry, because it provides manufacturing companies with a competitive advantage and makes production more efficient and sustainable. This study analyzes related literature on smart manufacturing, and summarizes five aspects of smart manufacturing and 29 criteria. The five aspects of smart manufacturing are smart design, smart production, smart factory, smart service, and industrial IoT management.
This study uses the Hierarchical Analysis Method (AHP) and the Decision Laboratory Analysis Method (DEMATEL). Two research methods are used to evaluate the weight and causality between smart manufacturing facets and guidelines. Based on the conclusions of the two, judge Taiwan's priority to develop Strategy. The research results show that the priority development of the five facets is the Industrial Internet of Things management. The criteria are as follows: First, the hardware prior to the development of sensors and software under the industrial Internet of Things management focus on rights management. After the combination of software and hardware, do device management and establish standard communication protocols. Second,The development of advanced process control is prioritized under the intelligent production structure, and the machine is intelligent after the best process of machine learning. Third, under the smart factory structure, digital transformation is prioritized, and IT infrastructure is updated or added based on the content of the digital transformation.The research results will provide Taiwan with a future development plan for smart manufacturing.
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