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Value Based and Intelligent Asset Management

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Cover of 'Value Based and Intelligent Asset Management'

Table of Contents

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    Book Overview
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    Chapter 1 Fundamental Concepts and Framework
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    Chapter 2 A Conceptual Framework for the Alignment of Infrastructure Assets to Citizen Requirements in Smart Cities
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    Chapter 4 Defining Asset Health Indicators (AHI) to Support Complex Assets Maintenance and Replacement Strategies. A Generic Procedure to Assess Assets Deterioration
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    Chapter 5 A Framework to Embed Asset Management in Production Companies
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    Chapter 6 An Approach to Value-Based Infrastructure Asset Management
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    Chapter 8 A CPS for Condition Based Maintenance Based on a Multi-agent System for Failure Modes Prediction in Grid Connected PV Systems
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    Chapter 9 Failure Mode Prediction and Energy Forecasting of PV Plants to Assist Maintenance Task by ANN Based Models
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    Chapter 10 Condition-Based Maintenance for Systems with Aging and Cumulative Damage Based on Proportional Hazards Model
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    Chapter 11 Implementation of a Condition Monitoring System on an Electric Arc Furnace Through a Risk-Based Methodology
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    Chapter 12 A Dynamic Opportunistic Maintenance Model to Maximize Energy-Based Availability While Reducing the Life Cycle Cost of Wind Farms
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    Chapter 13 A Review of the Roles of Digital Twin in CPS-Based Production Systems
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    Chapter 14 A Social Network of Collaborating Industrial Assets
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    Chapter 15 Collaborative Prognostics in Social Asset Networks
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    Chapter 17 Summary of Book Findings. Mapping Chapters to Framework Dimensions
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Citations

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Title
Value Based and Intelligent Asset Management
Published by
Springer International Publishing, August 2019
DOI 10.1007/978-3-030-20704-5
ISBNs
978-3-03-020703-8, 978-3-03-020704-5
Editors

Adolfo Crespo Márquez, Marco Macchi, Ajith Kumar Parlikad

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 55 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 14 25%
Student > Bachelor 8 15%
Student > Ph. D. Student 8 15%
Researcher 5 9%
Unspecified 1 2%
Other 1 2%
Unknown 18 33%
Readers by discipline Count As %
Engineering 16 29%
Business, Management and Accounting 14 25%
Energy 2 4%
Computer Science 1 2%
Unspecified 1 2%
Other 1 2%
Unknown 20 36%