Predictive Maintenance in Dynamic Systems Advanced Methods, Decision Support Tools and Real-World Applications /

This book provides a complete picture of several decision support tools for predictive maintenance. These include embedding early anomaly/fault detection, diagnosis and reasoning, remaining useful life prediction (fault prognostics), quality prediction and self-reaction, as well as optimization, con...

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Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Lughofer, Edwin (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Sayed-Mouchaweh, Moamar (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
Έκδοση:1st ed. 2019.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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245 1 0 |a Predictive Maintenance in Dynamic Systems  |h [electronic resource] :  |b Advanced Methods, Decision Support Tools and Real-World Applications /  |c edited by Edwin Lughofer, Moamar Sayed-Mouchaweh. 
250 |a 1st ed. 2019. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2019. 
300 |a XIII, 567 p. 200 illus., 144 illus. in color.  |b online resource. 
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505 0 |a Introduction -- Predictive Maintenance and (Early) FDD in Dynamic Systems -- Beyond State-of-the-Art -- Early Fault Detection and Diagnosis Approaches -- Prognostics and Forecasting -- Self-Reaction and Self-Healing Techniques -- Applications of Predictive Maintenance with emphasize on Industry 4.0 challenges -- Conclusion. 
520 |a This book provides a complete picture of several decision support tools for predictive maintenance. These include embedding early anomaly/fault detection, diagnosis and reasoning, remaining useful life prediction (fault prognostics), quality prediction and self-reaction, as well as optimization, control and self-healing techniques. It shows recent applications of these techniques within various types of industrial (production/utilities/equipment/plants/smart devices, etc.) systems addressing several challenges in Industry 4.0 and different tasks dealing with Big Data Streams, Internet of Things, specific infrastructures and tools, high system dynamics and non-stationary environments . Applications discussed include production and manufacturing systems, renewable energy production and management, maritime systems, power plants and turbines, conditioning systems, compressor valves, induction motors, flight simulators, railway infrastructures, mobile robots, cyber security and Internet of Things. The contributors go beyond state of the art by placing a specific focus on dynamic systems, where it is of utmost importance to update system and maintenance models on the fly to maintain their predictive power. . 
650 0 |a Electrical engineering. 
650 0 |a Quality control. 
650 0 |a Reliability. 
650 0 |a Industrial safety. 
650 0 |a Control engineering. 
650 0 |a Computational intelligence. 
650 0 |a Computers. 
650 1 4 |a Communications Engineering, Networks.  |0 http://scigraph.springernature.com/things/product-market-codes/T24035 
650 2 4 |a Quality Control, Reliability, Safety and Risk.  |0 http://scigraph.springernature.com/things/product-market-codes/T22032 
650 2 4 |a Control and Systems Theory.  |0 http://scigraph.springernature.com/things/product-market-codes/T19010 
650 2 4 |a Computational Intelligence.  |0 http://scigraph.springernature.com/things/product-market-codes/T11014 
650 2 4 |a Information Systems and Communication Service.  |0 http://scigraph.springernature.com/things/product-market-codes/I18008 
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700 1 |a Sayed-Mouchaweh, Moamar.  |e editor.  |4 edt  |4 http://id.loc.gov/vocabulary/relators/edt 
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