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Elsevier Reliability Analysis and Asset Management of Engineering Systems (Advances in Reliability Science)

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81 days 14 days · current 42 days 6 days 5 days 4 days 5 days 0 20 41 61 81 £130 £131 £133 £134 £143 £144 £145 Days at Price

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Description

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. Review Provides practical innovative methods that can be used to evaluate reliability and availability of complex systems, including simulation-based methods From the Back Cover 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. 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.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
24 September 2021
Listed Since
05 March 2021

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No barcode data available

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