Reliability, Risk and Safety: Back to the Future covers topics on reliability, risk and safety issues, including risk and reliability analysis methods, maintenance optimization, human factors, and risk management. The application areas range from nuclear engineering, oil and gas industry, electrical and civil engineering to information technology and communication, security, transportation, health and medicine or critical infrastructures. Significant attention is paid to societal factors influencing the use of reliability and risk assessment methods, and to combinatorial analysis, which has found its way into the analysis of probabilities and risk, from which quantified risk analysis developed. Integral demonstrations of the use of risk analysis and safety assessment are provided in many practical applications concerning major technological systems and structures. Reliability, Risk and Safety: Back to the Future will be of interest to academics and engineers interested in nuclear engineering, oil and gas engineering, electrical engineering, civil engineering, information technology, communication, and infrastructure.

Monte Carlo simulation is one of the best tools for performing realistic analysis of complex systems as it allows most of the limiting assumptions on system behavior to be relaxed. The Monte Carlo Simulation Method for System Reliability and Risk Analysis comprehensively illustrates the Monte Carlo simulation method and its application to reliability and system engineering. Readers are given a sound understanding of the fundamentals of Monte Carlo sampling and simulation and its application for realistic system modeling. Whilst many of the topics rely on a high-level understanding of calculus, probability and statistics, simple academic examples will be provided in support to the explanation of the theoretical foundations to facilitate comprehension of the subject matter. Case studies will be introduced to provide the practical value of the most advanced techniques. This detailed approach makes The Monte Carlo Simulation Method for System Reliability and Risk Analysis a key reference for senior undergraduate and graduate students as well as researchers and practitioners. It provides a powerful tool for all those involved in system analysis for reliability, maintenance and risk evaluations.

The safe management of the complex distributed systems and critical infrastructures which constitute the backbone of modern industry and society entails identifying and quantifying their vulnerabilities to design adequate protection, mitigation, and emergency action against failure. In practice, there is no fail-safe solution to such problems and various frameworks are being proposed to effectively integrate different methods of complex systems analysis in a problem-driven approach to their solution. Vulnerable Systems reflects the current state of knowledge on the procedures which are being put forward for the risk and vulnerability analysis of critical infrastructures. Classical methods of reliability and risk analysis, as well as new paradigms based on network and systems theory, including simulation, are considered in a dynamic and holistic way. Readers of Vulnerable Systems will benefit from its structured presentation of the current knowledge base on this subject. It will enable graduate students, researchers and safety and risk analysts to understand the methods suitable for different phases of analysis and to identify their criticalities in application.

Monte Carlo simulation is one of the best tools for performing realistic analysis of complex systems as it allows most of the limiting assumptions on system behavior to be relaxed. The Monte Carlo Simulation Method for System Reliability and Risk Analysis comprehensively illustrates the Monte Carlo simulation method and its application to reliability and system engineering. Readers are given a sound understanding of the fundamentals of Monte Carlo sampling and simulation and its application for realistic system modeling. Whilst many of the topics rely on a high-level understanding of calculus, probability and statistics, simple academic examples will be provided in support to the explanation of the theoretical foundations to facilitate comprehension of the subject matter. Case studies will be introduced to provide the practical value of the most advanced techniques. This detailed approach makes The Monte Carlo Simulation Method for System Reliability and Risk Analysis a key reference for senior undergraduate and graduate students as well as researchers and practitioners. It provides a powerful tool for all those involved in system analysis for reliability, maintenance and risk evaluations.

The safe management of the complex distributed systems and critical infrastructures which constitute the backbone of modern industry and society entails identifying and quantifying their vulnerabilities to design adequate protection, mitigation, and emergency action against failure. In practice, there is no fail-safe solution to such problems and various frameworks are being proposed to effectively integrate different methods of complex systems analysis in a problem-driven approach to their solution. Vulnerable Systems reflects the current state of knowledge on the procedures which are being put forward for the risk and vulnerability analysis of critical infrastructures. Classical methods of reliability and risk analysis, as well as new paradigms based on network and systems theory, including simulation, are considered in a dynamic and holistic way. Readers of Vulnerable Systems will benefit from its structured presentation of the current knowledge base on this subject. It will enable graduate students, researchers and safety and risk analysts to understand the methods suitable for different phases of analysis and to identify their criticalities in application.

Safety and Reliability of Complex Engineered Systems contains the Proceedings of the 25th European Safety and Reliability Conference, ESREL 2015, held 7-10 September 2015 in Zurich, Switzerland. It includes about 570 papers accepted for presentation at the conference. These contributions focus on theories and methods in the area of risk, safety and reliability, and their applications to a wide range of industrial, civil and social sectors. The main goal of this book is to showcase the advancements in understanding, modeling and management of complex engineered systems. The book offers a multidisciplinary platform to address technological, societal and financial aspects of system safety and reliability. Emphasis is given to the intra- and interdependencies of functions and the cascading failures that characterize complex engineered systems. Safety and Reliability of Complex Engineered Systems (abstracts book 730 pages + full paper CD-ROM 4634 pages) will be of interest to academics and professionals involved or interested in aspect of risk, safety and reliability in various engineering areas.

This book considers a broad range of areas from decision making methods applied in the contexts of Risk, Reliability and Maintenance (RRM). Intended primarily as an update of the 2015 book Multicriteria and Multiobjective Models for Risk, Reliability and Maintenance Decision Analysis, this edited work provides an integration of applied probability and decision making. Within applied probability, it primarily includes decision analysis and reliability theory, amongst other topics closely related to risk analysis and maintenance.  In decision making, it includes multicriteria decision making/aiding (MCDM/A) methods and optimization models. Within MCDM, in addition to decision analysis, some of the topics related to mathematical programming areas are considered, such as multiobjective linear programming, multiobjective nonlinear programming, game theory and negotiations, and multiobjective optimization. Methods related to these topics have been applied to the context of RRM. In MCDA, several other methods are considered, such as outranking methods, rough sets and constructive approaches.  The book addresses an innovative treatment of decision making in RRM, improving the integration of fundamental concepts from both areas of RRM and decision making. This is accomplished by presenting current research developments in decision making on RRM. Some pitfalls of decision models on practical applications on RRM are discussed and new approaches for overcoming those drawbacks are presented.

This book considers a broad range of areas from decision making methods applied in the contexts of Risk, Reliability and Maintenance (RRM). Intended primarily as an update of the 2015 book Multicriteria and Multiobjective Models for Risk, Reliability and Maintenance Decision Analysis, this edited work provides an integration of applied probability and decision making. Within applied probability, it primarily includes decision analysis and reliability theory, amongst other topics closely related to risk analysis and maintenance. In decision making, it includes multicriteria decision making/aiding (MCDM/A) methods and optimization models. Within MCDM, in addition to decision analysis, some of the topics related to mathematical programming areas are considered, such as multiobjective linear programming, multiobjective nonlinear programming, game theory and negotiations, and multiobjective optimization. Methods related to these topics have been applied to the context of RRM. In MCDA, several other methods are considered, such as outranking methods, rough sets and constructive approaches. The book addresses an innovative treatment of decision making in RRM, improving the integration of fundamental concepts from both areas of RRM and decision making. This is accomplished by presenting current research developments in decision making on RRM. Some pitfalls of decision models on practical applications on RRM are discussed and new approaches for overcoming those drawbacks are presented.

Safety is a major concern of society and touches on many areas of human activity. One important component of safety is the reliability of equipment and systems and the actions of the professionals, who design, build and operate them. Modelling methods have been developed to assess the risk associated with taking decisions relating to the design, maintenance or operation of a system. Such models include the element of uncertainty inherent in the behaviour of any given system. There are a number of theories, techniques and methods available, continuously being developed and improved, which evaluate the safety and reliability of systems, ensuring that these are operated and managed in a way as to keep the associated risks within the boundaries of what is considered tolerable or acceptable. These proceedings highlight the theories and methods used to assess safety and reliability, presenting them as powerful tools for decision-making which can be used effectively to manage the daily risks to which modern society is exposed.

The Handbook of RAMS in Railway Systems: Theory and Practice addresses the complexity in today's railway systems, which use computers and electromechanical components to increase efficiency while ensuring a high level of safety. RAM (Reliability, Availability, Maintainability) addresses the specifications and standards that manufacturers and operators have to meet. Modeling, implementation, and assessment of RAM and safety requires the integration of railway engineering systems; mathematical and statistical methods; standards compliance; and financial/economic factors. This Handbook brings together a group of experts to present RAM and safety in a modern, comprehensive manner.

Reliability and safety are fundamental attributes of any modern technological system. To achieve this, diverse types of protection barriers are placed as safeguards from the hazard posed by the operation of the system, within a multiple-barrier design concept. These barriers are intended to protect the system from failures of any of its elements, hardware, software, human and organizational. Correspondingly, the quantification of the probability of failure of the system and its protective barriers, through reliability and risk analyses, becomes a primary task in both the system design and operation phases. This exercise book serves as a complementary tool supporting the methodology concepts introduced in the books "An Introduction to the Basics of Reliability and Risk Analysis" and "Computational Methods for Reliability and Risk Analysis" by Enrico Zio, in that it gives an opportunity to familiarize with the applications of classical and advanced techniques of reliability and risk analysis. This book is also available as a set with "Computational Methods for Reliability and Risk Analysis" and "An Introduction to the Basics of Reliability and Risk Analysis."

This book illustrates a number of modelling and computational techniques for addressing relevant issues in reliability and risk analysis. In particular, it provides: i) a basic illustration of some methods used in reliability and risk analysis for modelling the stochastic failure and repair behaviour of systems, e.g. the Markov and Monte Carlo simulation methods; ii) an introduction to Genetic Algorithms, tailored to their application for RAMS (Reliability, Availability, Maintainability and Safety) optimization; iii) an introduction to key issues of system reliability and risk analysis, like dependent failures and importance measures; and iv) a presentation of the issue of uncertainty and of the techniques of sensitivity and uncertainty analysis used in support of reliability and risk analysis.

The book provides a technical basis for senior undergraduate or graduate courses and a reference for researchers and practitioners in the field of reliability and risk analysis. Several practical examples are included to demonstrate the application of the concepts and techniques in practice.

The necessity of expertise for tackling the complicated and multidisciplinary issues of safety and risk has slowly permeated into all engineering applications so that risk analysis and management has gained a relevant role, both as a tool in support of plant design and as an indispensable means for emergency planning in accidental situations. This entails the acquisition of appropriate reliability modeling and risk analysis tools to complement the basic and specific engineering knowledge for the technological area of application. Aimed at providing an organic view of the subject, this book provides an introduction to the principal concepts and issues related to the safety of modern industrial activities. It also illustrates the classical techniques for reliability analysis and risk assessment used in current practice.