eMaintenance - 1st Edition - ISBN: 9780128111536

eMaintenance

1st Edition

Essential Electronic Tools for Efficiency

Authors: Diego Galar
Paperback ISBN: 9780128111536
Imprint: Academic Press
Published Date: 30th June 2017
Page Count: 558
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Description

eMaintenance: Essential Electronic Tools for Efficiency is a practical guide for anyone interested in running a plant as a smart asset. The book explores how to improve and enhance efficiency of operations, maintenance staff, infrastructure managers, and system integrators using a real time computerized system from data to decision.

In recent years we have seen the exciting possibilities of eMaintenance become a recognized source of productivity improvement in industry. The seamless linking of systems and equipment to control centres for real time reconfiguring is improving efficiency, reliability, and sustainability in a variety of settings. Methods of overcoming the challenges of data collection and processing are explained before the introduction of tools for data driven condition monitoring and decision making.

Key Features

  • Includes links to eMaintenance applications and MATLAB code which can be downloaded and used
  • Provides an introduction to collecting and processing data from machinery
  • Explains how to use sensor-based tools to increase efficiency of diagnosis, prognosis, and decision-making in maintenance
  • Describes methods for overcoming the challenges of data collection and processing

Readership

Reliability and Maintenance Engineers with an interest in Industry 4.0. Researchers in the field of Industry 4.0, manufacturing, and machinery

Table of Contents

1. Sensors and data acquisition
1.1 Sensor level in maintenance: A need for information integration
1.2 Sensor fusion
1.3 Sensors network: A distributed approach in large assets
1.4 SMART sensors
1.5 Energy harvesting for sensors and configuration issues
2. Data collection
2.1 Data representation
2.1 Data cleaning
2.2 Data sanitization
2.3 Data compression and transmission
3. Pre-processing  and features
3.1 Time and frequency domains for data representation
3.2 Feature selection
3.3 Feature extraction
4. Data and information fusion from disparate AM (Asset Management sources)
4.1 On line and off line condition monitoring information
4.2 CMMS Computer Maintenance Management Systems
4.3 SCADA and automation data from PLC and similar devices
4.4 ERP and other cooperate information related to the asset
5. Diagnosis
5.1 The goals for detection, identification and localization of failures
5.2 Data driven versus physical models
5.3 Supervised, semi supervised and unsupervised: Issues and challenges  of failure catalogues
5.4 The concept of NFF Non Fault Found and the issues of complex systems
6. Prognosis
6.1 Definition of RUL (remaining useful life): economic, service and physical approaches
6.12 Model based, data driven, symbolic and hybrid models
6.3 Uncertainty management in RUL (remaining useful life) estimation
6.4 RUL in complex systems: From component to system level and fleet level
7. Maintenance DSS (decision support systems)
7.1 A new era in Industry 4.0: Maintenance 4.0
7.2 Virtualization and emulation: The e-factory for fault rate reduction
7.3 Multivariate maintenance decision support: A consequence of Internet of Things (IoT)
7.4 The end of traditional maintenance approaches: Real time decisions based on industrial big data
7.5 The revenue of e-Maintenance and maintenance 4.0: Technology impact on operation and maintenance  KPIs
8. Actuators and self-maintenance approaches
8.1 Intelligent materials for maintenance
8.2 SMART devices with actuation capabilities: SMART bearings
8.3 Robotics in maintenance duties

Details

No. of pages:
558
Language:
English
Copyright:
© Academic Press 2017
Published:
Imprint:
Academic Press
Paperback ISBN:
9780128111536

About the Author

Diego Galar

Diego Galar is Professor of Reliability and Maintenance in Skovde University, holding the VOLVO chair for maintenance, and Professor of Condition Monitoring in the Division of Operation and Maintenance Engineering at LTU, Luleå University of Technology, and was also involved in the SKF UTC centre focused on SMART bearings. He is also actively involved in national projects with Swedish industry. In industry, he has been technological director and CBM manager of international companies, and actively participated in national and international committees for standardization and R&D in the topics of reliability and maintenance.

Affiliations and Expertise

Professor of Reliability and Maintenance, Skovde University, Sweden