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Data intensive industrial asset mana...

Balali, Farhad.

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Data intensive industrial asset management = IoT-based algorithms and implementation /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Data intensive industrial asset management/ by Farhad Balali ... [et al.].
其他題名:	IoT-based algorithms and implementation /
其他作者:	Balali, Farhad.
出版者:	Cham :Springer International Publishing : : 2020.,
面頁冊數:	xxi, 236 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer eBooks
標題:	Internet of things. -
電子資源:	https://doi.org/10.1007/978-3-030-35930-0
ISBN:	9783030359300

Data intensive industrial asset management = IoT-based algorithms and implementation /
Data intensive industrial asset managementIoT-based algorithms and implementation /[electronic resource] :by Farhad Balali ... [et al.]. - Cham :Springer International Publishing :2020. - xxi, 236 p. :ill., digital ;24 cm.

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.

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.

ISBN: 9783030359300

Standard No.: 10.1007/978-3-030-35930-0doiSubjects--Topical Terms:

2057703
Internet of things.

LC Class. No.: TK5105.8857

Dewey Class. No.: 004.678

Data intensive industrial asset management = IoT-based algorithms and implementation /
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505 0 $a 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.
520 $a 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.
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