This book compiles and critically discusses modern engineering system degradation models and their impact on engineering decisions. In particular, the authors focus on modeling the uncertain nature of degradation considering both conceptual discussions and formal mathematical formulations. It also describes the basics concepts and the various modeling aspects of life-cycle analysis (LCA). It highlights the role of degradation in LCA and defines optimum design and operation parameters. Given the relationship between operational decisions and the performance of the system's condition over time, maintenance models are also discussed.

The concepts and models presented have applications in a large variety of engineering fields such as Civil, Environmental, Industrial, Electrical and Mechanical engineering. However, special emphasis is given to problems related to large infrastructure systems. The book is intended to be used both as a reference resource for researchers and practitioners and as an academic text for courses related to risk and reliability, infrastructure performance modeling and life-cycle assessment.

Autorentext

Mauricio Sánchez-Silva: Professor of the Civil and Environmental Engineering Department at Los Andes University (Bogotá, Colombia) since 1996. Dr. Sánchez-Silva received his B.S. and MSc. in Civil engineering from Los Andes University; and the Ph.D. at the University of Bristol, UK. The main areas of research of Dr. Sánchez-Silva are: applied probability (risk and reliability assessment), life-cycle analysis, and physical and stochastic modelling of degrading systems; areas which are all related with the topic of this book. The result of his research has led to the publication of numerous journal and conference papers, several book chapters and two books. Most of these publications are related to infrastructure problems such as degradation (e.g., chloride ingress in concrete, biodegradation, stochastic modelling), maintenance (optimum infrastructure operation policies), risk and reliability assessment, and network modelling. In addition, Dr. Sánchez-Silva has taught both graduate and undergraduate courses in Civil and Industrial Engineering; graduate courses are mostly related to risk, reliability and infrastructure management and modeling. Finally, he has been involved in projects with different industrial sectors (e.g., oil industry; construction, disaster management offices), which involve risk and reliability assessments and the evaluation of infrastructure's performance over time.

Georgia-Ann Klutke: Professor of Industrial and SystemsEngineering at Texas A&M University. Dr. Klutke received her B.S. in mathematics and M.S. in biostatistics from the University of Michigan, and Ph.D. in industrial engineering and operations research from the Virginia Polytechnic Institute and State University. The research interests of Dr. Klutke are in the applications of probabilistic methods in engineering, primarily focused on production operations, and particularly in equipment reliability and maintenance. Dr. Klutke has published widely in this area and have taught a variety of courses ranging from probabilistic methods, beginning and advanced stochastic processes, production operations, to reliability and maintenance engineering. She has also served on the faculties of the University of Massachusetts, Amherst, The University of Texas at Austin, and have been full Professor at Texas A&M since 2002. Her research has been funded by the U.S. National Science Foundation, U.S. National Aeronautics and Space Administration, State of Texas, and General Motors Research Lab, among others. Dr. Klutke is a Registered Professional Engineering in the State of Texas and an elected Fellow of the Institute of Industrial Engineers.

Inhalt

Engineering decisions for long term performance of systems.- Reliability of engineered systems.- Basics of stochastic processes, point and marked point processes.- Degradation: data analysis and analytical modeling.- Continuous state degradation models.- Discrete state degradation models.- A generalized approach to degradation.- Systematically reconstructed systems.