Shows the multifaceted and interactive character of the relationship between science and technology on the one hand, and business and innovation on the other. This book explores this non-linear relationship through a selection of case studies and discusses its implications for science as well as for business.
CRM Systems in Industrial Companies contributes new knowledge on Customer Relationship Management (CRM) in the field of industrial marketing. Based on an in-depth case study, this book highlights the complexity and challenges in the development, implementation and use of CRM, revealing how truly challenging it is to extract value from CRM systems.
Explores methods for the representation and treatment of uncertainty in risk assessment In 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.
eliability 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.
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.
Explores methods for the representation and treatment of uncertainty in risk assessment In 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.
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.
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.
Enrico Michelini illustrates that sport plays a very marginal role in the contemporary health promotion. This is the main result of the present analysis of national strategies for the promotion of physical activity issued by the health ministries of France, Germany, and Italy. All these health-strategies are rather ambiguous on this subject: They mention sport systematically as an abstract term, but they marginalise it as a medium of health in its traditional-competitive form. As a consequence, while sport has generally been considered healthy over a long period in the past, most health organisations today recommend only moderate physical activity as conducive to good health. The author examines this paradigmatic change in the international discussion about the forms of health-enhancing physical activity through a theoretical framework based on Luhmann’s systems theory.
Shows the multifaceted and interactive character of the relationship between science and technology on the one hand, and business and innovation on the other. This book explores this non-linear relationship through a selection of case studies and discusses its implications for science as well as for business.
Drawing on original research, this book looks at what sport can tell us about the social processes, patterns and outcomes of forced migration and the 'refugee crisis'. Adopting a systems theory framework and examining different sport disciplines, performance levels and settings, it represents a significant contribution to our understanding of one of the most urgent social issues facing the modern world. The book explores four key aspects of sport’s intersection with forced migration. Firstly, it looks at how the media covers sport in relation to the 'refugee crisis', specifically coverage of refugee elite athletes. Secondly, it examines the adaptation of sport organisations to the 'refugee crisis', including the culture, programmes and structures that promote or obstruct sport for refugees. Thirdly, the book looks at sport in refugee sites, and how sport can be used as therapy, an escape or empowerment for refugees but also how it can reinforce the divisions between staff and the refugees themselves. Finally, the book looks at how forced migration influences and is influenced by participation in elite sport, by examining the biographies of elite migrant athletes. A richly descriptive, critical and illuminating piece of work, this book is fascinating reading for anybody with an interest in sport, migration, sociology or the relationship between sport and wider society. The Open Access version of this book, available at www. taylorfrancis.com, has been made available under a Creative Commons Attribution 4.0 license.
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.
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.
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