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Record Nr. |
UNINA9910373904703321 |
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Autore |
Balali Farhad |
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Titolo |
Data Intensive Industrial Asset Management : IoT-based Algorithms and Implementation / / by Farhad Balali, Jessie Nouri, Adel Nasiri, Tian Zhao |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (XXI, 236 p. 132 illus., 126 illus. in color.) |
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Disciplina |
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Soggetti |
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Quality control |
Reliability |
Industrial safety |
Buildings—Design and construction |
Building |
Construction |
Engineering, Architectural |
Statistics |
Quality Control, Reliability, Safety and Risk |
Building Construction and Design |
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Principles of Internet of Things (IoT) -- Asset Management and Maintenance Policies -- Statistical Data Analysis -- Descriptive, Diagnostics, Predictive, and Prescriptive Analysis -- Fault and Risk Analysis -- Predictive Failure Detection Algorithms -- Smart Device Function and Operation -- Data Driven Approaches -- Parameter Selection and Real Time Monitoring -- Edge and Cloud Computing -- Data Analytics and Visualization -- Artificial Intelligence for Predictive Maintenance -- Implementation Tools -- Case Studies. |
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Sommario/riassunto |
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This book presents a step by step Asset Health Management Optimization Approach Using Internet of Things (IoT). The authors |
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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. |
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