Intelligent Machinery Fault Diagnostics and Prognostics : The Future of Smart Manufacturing
Book Details
Format
Paperback / Softback
ISBN-10
1032770090
ISBN-13
9781032770093
Publisher
Taylor & Francis Ltd
Imprint
CRC Press
Country of Manufacture
GB
Country of Publication
GB
Publication Date
Jul 19th, 2026
Print length
270 Pages
Weight
530 grams
Product Classification:
Product designRisk assessmentProduction & quality control managementProduction and quality control managementManufacturing industriesProbability & statisticsProbability and statisticsMathematical modellingEngineering: generalErgonomicsMechanical engineeringHydraulic engineering
Ksh 10,100.00
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Intelligent Machinery Fault Diagnostics and Prognostics: The Future of Smart Manufacturing uses an interdisciplinary approach to provide a well-rounded understanding of smart manufacturing.
The field of machinery maintenance is undergoing a remarkable transformation, driven by the convergence of intelligent technologies and data-driven approaches. This book delves into the fascinating world of intelligent machinery fault diagnostics and prognostics, exploring how these advancements are reshaping the way we monitor, diagnose, and predict faults in machinery. Intelligent Machinery Fault Diagnostics and Prognostics: The Future of Smart Manufacturing uses an interdisciplinary approach to provide a well-rounded understanding of smart manufacturing. It discusses cutting-edge smart manufacturing technologies and encompasses various aspects, from sensors and data analytics to predictive maintenance. The book offers real-world case studies illustrating how these innovations are successfully implemented in industrial settings and includes practical guidelines and methodologies that facilitate the implementation of solutions. The book also highlights the scalability and adaptability of this approach to different industries and manufacturing environments. Whether this book is for industry professionals, students, or researchers, readers can leverage the book’s insights to optimize machinery performance, minimize downtime, reduce costs, and improve safety in their respective industries.
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