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Data Intensive Industrial Asset Management : IoT-based Algorithms and Implementation / by Farhad Balali, Jessie Nouri, Adel Nasiri, Tian Zhao.

1st ed. 2020.

9783030359300
3030359301
9783030359294
3030359298
9783030359294
9783030359317 (print)
303035931X
9783030359324 (print)
3030359328

Cham : Springer International Publishing, 2020 : Imprint Springer.

English

1 online resource (XXI, 236 pages 132 illustrations, 126 illustrations in color.) : online resource

10.1007/978-3-030-35930-0

TA169.7 .D38 2020eb

658.56

This book presents a step by step Asset Health Management Optimization Approach Using Internet of Things (IoT). The authors provide a comprehensive study which includes the descriptive, diagnostic, predictive, and prescriptive analysis in detail. The presentation focuses on the challenges of the parameter selection, statistical data analysis, predictive algorithms, big data storage and selection, data pattern recognition, machine learning techniques, asset failure distribution estimation, reliability and availability enhancement, condition based maintenance policy, failure detection, data driven optimization algorithm, and a multi-objective optimization approach, all of which can significantly enhance the reliability and availability of the system. Provides a comprehensive reference, focused on the Asset Health Management Optimization Approach Using Internet of Things (IoT); Describes a data-driven optimization method, which considers the challenges raise by big data analysis; Enables a multi-objective approach, which includes the healthy index, reliability, availability, and cost, with respect to the optimization methods and computational restrictions which can have various applications.

Includes bibliographical references and index.

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