Enrico Zio – författare

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.

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.

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.

Explores methods for the representation and treatment of uncertainty in risk assessmentIn providing guidance for practical decision-making situations concerning high-consequence technologies (e.g., nuclear, oil and gas, transport, etc.), the theories and methods studied in Uncertainty in Risk Assessment have wide-ranging applications from engineering and medicine to environmental impacts and natural disasters, security, and financial risk management. The main focus, however, is on engineering applications.While requiring some fundamental background in risk assessment, as well as a basic knowledge of probability theory and statistics, Uncertainty in Risk Assessment can be read profitably by a broad audience of professionals in the field, including researchers and graduate students on courses within risk analysis, statistics, engineering, and the physical sciences.Uncertainty in Risk Assessment: Illustrates the need for seeing beyond probability to represent uncertainties in risk assessment contexts.Provides simple explanations (supported by straightforward numerical examples) of the meaning of different types of probabilities, including interval probabilities, and the fundamentals of possibility theory and evidence theory.Offers guidance on when to use probability and when to use an alternative representation of uncertainty.Presents and discusses methods for the representation and characterization of uncertainty in risk assessment.Uses examples to clearly illustrate ideas and concepts.

This book offers a comprehensive overview of recently developed methods for assessing and optimizing system reliability. It consists of two main parts, for treating assessment methods and optimization methods, respectively.The first part covers methods of multi-state system reliability modelling and evaluation, Markov processes, Monte Carlo simulation and uncertainty analysis. The methods considered range from piecewise-deterministic Markov processes to belief function analysis. The second part covers optimization methods of mathematical programming and evolutionary algorithms, and problems of multi-objective optimization and optimization under uncertainty. The methods of this part range from non-dominated sorting genetic algorithm to robust optimization.The book also includes the application of the assessment and optimization methods considered on real case studies, particularly with respect to the reliability assessment and optimization of renewable energy systems, and bridges the gap between theoretical method development and engineering practice.

Exciting new developments in risk assessment and managementRisk assessment and management is fundamentally founded on the knowledge available on the system or process under consideration. While this may be self-evident to the laymen, thought leaders within the risk community have come to recognize and emphasize the need to explicitly incorporate knowledge (K) in a systematic, rigorous, and transparent framework for describing and modeling risk.Featuring contributions by an international team of researchers and respected practitioners in the field, this book explores the latest developments in the ongoing effort to use risk assessment as a means for characterizing knowledge and/or lack of knowledge about a system or process of interest. By offering a fresh perspective on risk assessment and management, the book represents a significant contribution to the development of a sturdier foundation for the practice of risk assessment and for risk-informed decision making.How should K be described and evaluated in risk assessment? How can it be reflected and taken into account in formulating risk management strategies? With the help of numerous case studies and real-world examples, this book answers these and other critical questions at the heart of modern risk assessment, while identifying many practical challenges associated with this explicit framework. This book, written by international scholars and leaders in the field, and edited to make coverage both conceptually advanced and highly accessible: Offers a systematic, rigorous and transparent perspective and framework on risk assessment and management, explicitly strengthening the links between knowledge and riskClearly and concisely introduces the key risk concepts at the foundation of risk assessment and managementFeatures numerous cases and real-world examples, many of which focused on various engineering applications across an array of industriesKnowledge of Risk Assessment and Management is a must-read for risk assessment and management professionals, as well as graduate students, researchers and educators in the field. It is also of interest to policy makers and business people who are eager to gain a better understanding of the foundations and boundaries of risk assessment, and how its outcomes should be used for decision-making.

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.

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.

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 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.

This book considers a broad range of areas from decision making methods applied in the contexts of Risk, Reliability and Maintenance (RRM). 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 book considers a broad range of areas from decision making methods applied in the contexts of Risk, Reliability and Maintenance (RRM). 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 handbook analyzes and develops methods and models to optimize solutions for energy access (for industry and the general world population alike) in terms of reliability and sustainability. With a focus on improving the performance of energy systems, it brings together state-of-the-art research on reliability enhancement, intelligent development, simulation and optimization, as well as sustainable development of energy systems. It helps energy stakeholders and professionals learn the methodologies needed to improve the reliability of energy supply-and-demand systems, achieve more efficient long-term operations, deal with uncertainties in energy systems, and reduce energy emissions.Highlighting novel models and their applications from leading experts in this important area, this book will appeal to researchers, students, and engineers in the various domains of smart energy systems and encourage them to pursue research and development in this exciting and highly relevant field.

This book summarizes the advanced intelligent pipeline management technologies. The text discusses the main challenges of how to define and reinvent data-driven intelligent pipeline systems by studying scheduling-operation- safety management systems. Additionally, within an all-around intelligent pipeline system technology development framework, this book characterizes the scientific problems of intelligent pipeline system services among different processes, such as scheduling, demand-side management, operation condition monitoring, safety analysis, fault detection, etc. This book also introduces the existing positive and successful intelligent pipeline system projects that can be identified in the studied domain, and how can they be best applied for practical success. The text is supported by informative illustrations and case studies so that practitioners can use the book as a toolbox to improve understanding in applying the novel technologies into intelligent pipeline systemmanagement and development.

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.

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.