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Herausgeber: 
  • Myeongsu Kang
  • Pecht Michael G.
  • Prognostics and Health Management of Electronics: Fundamentals, Machine Learning, and the Internet of Things 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  September 2018  
    Genre:  Naturwissensch., Medizin, Technik 
     
    condition-based (predictive) maintenance / cut life-cycle costs of equipment / Electronics engineering / how to assess the cost and benefits of prognostic implementations / how to increase system availability by extending maintenance cycles or repairs / how to reduce no fault found (NFF) occurrence / in situ monitoring methods of systems in life-cycle conditions / load history for future design, qualification, and root cause analysis
    ISBN:  9781119515333 
    EAN-Code: 
    9781119515333 
    Verlag:  Wiley 
    Einband:  Gebunden  
    Sprache:  English  
    Serie:  Wiley - IEEE  
    Dimensionen:  H 246 mm / B 173 mm / D 51 mm 
    Gewicht:  1542 gr 
    Seiten:  800 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:

    AN INDISPENSABLE GUIDE FOR ENGINEERS AND DATA SCIENTISTS IN DESIGN, TESTING, OPERATION, MANUFACTURING, AND MAINTENANCE

    A road map to the current challenges and available opportunities for the research and development of Prognostics and Health Management (PHM), this important work covers all areas of electronics and explains how to:

    • assess methods for damage estimation of components and systems due to field loading conditions
    • assess the cost and benefits of prognostic implementations
    • develop novel methods for in situ monitoring of products and systems in actual life-cycle conditions
    • enable condition-based (predictive) maintenance
    • increase system availability through an extension of maintenance cycles and/or timely repair actions
    • obtain knowledge of load history for future design, qualification, and root cause analysis
    • reduce the occurrence of no fault found (NFF)
    • subtract life-cycle costs of equipment from reduction in inspection costs, downtime, and inventory

    Prognostics and Health Management of Electronics also explains how to understand statistical techniques and machine learning methods used for diagnostics and prognostics. Using this valuable resource, electrical engineers, data scientists, and design engineers will be able to fully grasp the synergy between IoT, machine learning, and risk assessment.

      



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