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Predictive Maintenance in Smart Factories [electronic resource] : Architectures, Methodologies, and Use-cases / edited by Tania Cerquitelli, Nikolaos Nikolakis, Niamh O’Mahony, Enrico Macii, Massimo Ippolito, Sotirios Makris.

Contributor(s): Material type: TextSeries: Information Fusion and Data SciencePublisher: Singapore : Springer Nature Singapore : Imprint: Springer, 2021Edition: 1st ed. 2021Description: XIV, 234 p. 117 illus., 108 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9789811629402
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 530.1 23
LOC classification:
  • Q295
Online resources:
Contents:
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.
In: Springer Nature eBookSummary: 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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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.

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.