Reliability Analysis and Asset Management of Engineering Systems

Reliability Analysis and Asset Management of Engineering Systems explains methods that can be used to evaluate reliability and availability of complex systems, including simulation-based methods.

The increasing digitization of mechanical processes driven by Industry 4.0 increases the interaction between machines and monitoring and control systems, leading to increases in system complexity. For those systems the reliability and availability analyses are increasingly challenging, as the interaction between machines has become more complex, and the analysis of the flexibility of the production systems to respond to machinery failure may require advanced simulation techniques.

This book fills a gap on how to deal with such complex systems by linking the concepts of systems reliability and asset management, and then making these solutions more accessible to industry by explaining the availability analysis of complex systems based on simulation methods that emphasise Petri nets.

  • Explains how to use a monitoring database to perform important tasks including an update of complex systems reliability
  • Shows how to diagnose probable machinery-based causes of system performance degradation by using a monitoring database and reliability estimates in an integrated way
  • Describes practical techniques for the application of AI and machine learning methods to fault detection and diagnosis problems
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Reliability Analysis and Asset Management of Engineering Systems

Reliability Analysis and Asset Management of Engineering Systems explains methods that can be used to evaluate reliability and availability of complex systems, including simulation-based methods.

The increasing digitization of mechanical processes driven by Industry 4.0 increases the interaction between machines and monitoring and control systems, leading to increases in system complexity. For those systems the reliability and availability analyses are increasingly challenging, as the interaction between machines has become more complex, and the analysis of the flexibility of the production systems to respond to machinery failure may require advanced simulation techniques.

This book fills a gap on how to deal with such complex systems by linking the concepts of systems reliability and asset management, and then making these solutions more accessible to industry by explaining the availability analysis of complex systems based on simulation methods that emphasise Petri nets.

  • Explains how to use a monitoring database to perform important tasks including an update of complex systems reliability
  • Shows how to diagnose probable machinery-based causes of system performance degradation by using a monitoring database and reliability estimates in an integrated way
  • Describes practical techniques for the application of AI and machine learning methods to fault detection and diagnosis problems
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Overview

Reliability Analysis and Asset Management of Engineering Systems explains methods that can be used to evaluate reliability and availability of complex systems, including simulation-based methods.

The increasing digitization of mechanical processes driven by Industry 4.0 increases the interaction between machines and monitoring and control systems, leading to increases in system complexity. For those systems the reliability and availability analyses are increasingly challenging, as the interaction between machines has become more complex, and the analysis of the flexibility of the production systems to respond to machinery failure may require advanced simulation techniques.

This book fills a gap on how to deal with such complex systems by linking the concepts of systems reliability and asset management, and then making these solutions more accessible to industry by explaining the availability analysis of complex systems based on simulation methods that emphasise Petri nets.

  • Explains how to use a monitoring database to perform important tasks including an update of complex systems reliability
  • Shows how to diagnose probable machinery-based causes of system performance degradation by using a monitoring database and reliability estimates in an integrated way
  • Describes practical techniques for the application of AI and machine learning methods to fault detection and diagnosis problems

Product Details

ISBN-13: 9780128235225
Publisher: Elsevier Science
Publication date: 09/24/2021
Series: Advances in Reliability Science
Sold by: Barnes & Noble
Format: eBook
Pages: 318
File size: 19 MB
Note: This product may take a few minutes to download.

About the Author

Gilberto Francisco Martha de Souza is an associate professor at the Department of Mechatronics and Mechanical Systems,
Escola Politécnica – University of São Paulo, Brazil. He is also the leader of the Reliability and Risk Analysis Laboratory, and has led a number of research projects aiming at defining risk-based maintenance planning of complex systems to improve system reliability and availability such as power plants (hydro and thermal), topside oil rigs equipment and mechanical equipment. He is currently associate editor of the journal ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering.
Arthur Henrique de Andrade Melani is a Brazilian-born and based engineer and academic researcher. He graduated (2013) as Mechatronics Engineer at the University of Sao Paulo and holds a Master’s degree (2015) and a Ph.D. (2020) in Mechanical Engineering from the same university. Since his graduation, he has actively participated in several research projects on Reliability Centered Maintenance, Fault Detection and Diagnosis, and Asset Management. His research has been mainly applied in the power generation sector, especially in hydroelectric and thermoelectric plants. He is currently a postdoctoral scholar at the Polytechnic School of the University of Sao Paulo.
Miguel Angelo De Carvalho Michalski works in the Department de Engenharia Mecatrônicae de Sistemas Mecanicos in Cidade Universitaria, Sau Paulo, Brazil.
Renan Favarao Da Silva works in the Dept de Engenharia Mecatrônica e de Sistemas Mecânicos at Cidade Universitaria in Sau Paulo, Brazil.

Table of Contents

1. Introduction to Reliability Analysis and Asset Management of Engineering Systems
2. Reliability and Maintenance Fundamentals
3. Engineering Systems Fundamentals
4. Systems Reliability and Availability Analysis
5. Engineering Systems Fault Detection Methods
6. Engineering Systems Fault Diagnosis Methods
7. Framework for Systems Health Monitoring and Fault Diagnosis
8. Engineering Systems Asset Management
9. Examples of Applications of Reliability Analysis and Asset Management of Engineering Systems
10. Conclusion: Reliability Analysis and Asset Management of Engineering Systems

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