資料來源:
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Predictive maintenance in smart factories architectures, methodologies, and use-cases / [electronic resource] :
- 其他作者:
- 其他題名:
- Information fusion and data science.
- 出版: Singapore : Springer Singapore :Imprint: Springer
- 叢書名: Information fusion and data science,
- 主題: Plant maintenance--Technological innovations. , Predictive control. , Data-driven Science, Modeling and Theory Building. , Communications Engineering, Networks. , Information Systems and Communication Service. , Computational Intelligence. , Quality Control, Reliability, Safety and Risk.
- ISBN: 9789811629402 (electronic bk.) 、 9789811629396 (paper)
- FIND@SFXID: CGU
- 資料類型: 電子書
- 內容註: 1. Industrial digitisation and maintenance: Present and Future -- 2. A hybrid cloud-to-edge predictive maintenance platform -- 3. Data-driven predictive maintenance: a methodology primer -- 4. Services to facilitate predictive maintenance in Industry4.0 -- 5. Predictive analytics in robotic industry.
- 摘要註: This book presents the outcome of the European project "SERENA", involving fourteen partners as international academics, technological companies, and industrial factories, addressing the design and development of a plug-n-play end-to-end cloud architecture, and enabling predictive maintenance of industrial equipment to be easily exploitable by small and medium manufacturing companies with a very limited data analytics experience. Perspectives and new opportunities to address open issues on predictive maintenance conclude the book with some interesting suggestions of future research directions to continue the growth of the manufacturing intelligence.
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讀者標籤:
- 系統號: 005538747 | 機讀編目格式
館藏資訊
This book presents the outcome of the European project "SERENA", involving fourteen partners as international academics, technological companies, and industrial factories, addressing the design and development of a plug-n-play end-to-end cloud architecture, and enabling predictive maintenance of industrial equipment to be easily exploitable by small and medium manufacturing companies with a very limited data analytics experience. Perspectives and new opportunities to address open issues on predictive maintenance conclude the book with some interesting suggestions of future research directions to continue the growth of the manufacturing intelligence.
資料來源:
Google Book
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