Data Intensive Industrial Asset Management - IoT-based Algorithms and Implementation (Hardcover, 1st ed. 2020)

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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.

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Product Description

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.

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Product Details

General

Imprint

Springer Nature Switzerland AG

Country of origin

Switzerland

Release date

2020

Availability

Expected to ship within 10 - 15 working days

First published

2020

Authors

, , ,

Dimensions

235 x 155mm (L x W)

Format

Hardcover

Pages

236

Edition

1st ed. 2020

ISBN-13

978-3-03-035929-4

Barcode

9783030359294

Categories

LSN

3-03-035929-8



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