Since the first edition of this book published, Bayesian networks have become even more important for applications in a vast array of fields. This second edition includes new material on influence diagrams, learning from data, value of information, cybersecurity, debunking bad statistics, and much more. Focusing on practical real-world problem-solving and model building, as opposed to algorithms and theory, it explains how to incorporate knowledge with data to develop and use (Bayesian) causal models of risk that provide more powerful insights and better decision making than is possible from purely data-driven solutions. Features Provides all tools necessary to build and run realistic Bayesian network models Supplies extensive example models based on real risk assessment problems in a wide range of application domains provided; for example, finance, safety, systems reliability, law, forensics, cybersecurity and more Introduces all necessary mathematics, probability, and statistics as needed Establishes the basics of probability, risk, and building and using Bayesian network models, before going into the detailed applications A dedicated website contains exercises and worked solutions for all chapters along with numerous other resources. The AgenaRisk software contains a model library with executable versions of all of the models in the book. Lecture slides are freely available to accredited academic teachers adopting the book on their course.

Although many Bayesian Network (BN) applications are now in everyday use, BNs have not yet achieved mainstream penetration. Focusing on practical real-world problem solving and model building, as opposed to algorithms and theory, Risk Assessment and Decision Analysis with Bayesian Networks explains how to incorporate knowledge with data to develop and use (Bayesian) causal models of risk that provide powerful insights and better decision making. Provides all tools necessary to build and run realistic Bayesian network models Supplies extensive example models based on real risk assessment problems in a wide range of application domains provided; for example, finance, safety, systems reliability, law, and more Introduces all necessary mathematics, probability, and statistics as needed The book first establishes the basics of probability, risk, and building and using BN models, then goes into the detailed applications. The underlying BN algorithms appear in appendices rather than the main text since there is no need to understand them to build and use BN models. Keeping the body of the text free of intimidating mathematics, the book provides pragmatic advice about model building to ensure models are built efficiently. A dedicated website, www.BayesianRisk.com, contains executable versions of all of the models described, exercises and worked solutions for all chapters, PowerPoint slides, numerous other resources, and a free downloadable copy of the AgenaRisk software.

This book presents a bibliographical review of the use of Bayesian networks in reliability over the last decade. Bayesian network (BN) is considered to be one of the most powerful models in probabilistic knowledge representation and inference, and it is increasingly used in the field of reliability. After focusing on the engineering systems, the book subsequently discusses twelve important issues in the BN-based reliability methodologies, such as BN structure modeling, BN parameter modeling, BN inference, validation, and verification. As such, it is a valuable resource for researchers and practitioners in the field of reliability engineering.

This book derives from the Special Issue of the Manufacturing Engineering Society 2019 (SIMES-2019) that has been launched as a joint issue of the journals Materials and Applied Sciences. The 29 contributions published in this Special Issue of Materials present cutting-edge advances in the field of manufacturing engineering focusing on additive manufacturing and 3D printing; advances and innovations in manufacturing processes; sustainable and green manufacturing; manufacturing of new materials; metrology and quality in manufacturing; industry 4.0; design, modeling, and simulation in manufacturing engineering; and manufacturing engineering and society. Among them, the topic "Additive Manufacturing and 3D Printing" has attracted a large number of contributions in this journal due to its widespread popularity and potential.

Operational risk assessment The Commercial Imperative of a More Forensic and Transparent Approach Brendon Young and Rodney Coleman “Brendon Young and Rodney Coleman's book is extremely timely. There has never been a greater need for the financial industry to reassess the way it looks at risk. [...] They are right to draw attention to the current widespread practices of risk management, which [...] have allowed risk to become underpriced across the entire industry.” Rt Hon John McFall MP, Chairman, House of Commons Treasury Committee Failure of the financial services sector to properly understand risk was clearly demonstrated by the recent 'credit crunch'. In its 2008 Global Stability Report, the IMF sharply criticised banks and other financial institutions for the failure of risk management systems, resulting in excessive risk-taking. Financial sector supervision and regulation was also criticised for lagging behind shifts in business models and rapid innovation. This book provides investors with a sound understanding of the approaches used to assess the standing of firms and determine their true potential (identifying probable losers and potential longer-term winners). It advocates a 'more forensic' approach towards operational risk management and promotes transparency, which is seen as a facilitator of competition and efficiency as well as being a barrier to fraud, corruption and financial crime. Risk assessment is an integral part of informed decision making, influencing strategic positioning and direction. It is fundamental to a company’s performance and a key differentiator between competing management teams. Increasing complexity is resulting in the need for more dynamic, responsive approaches to the assessment and management of risk. Not all risks can be quantified; however, it remains incumbent upon management to determine the impact of possible risk-events on financial statements and to indicate the level of variation in projected figures. To begin, the book looks at traditional methods of risk assessment and shows how these have developed into the approaches currently being used. It then goes on to consider the more advanced forensic techniques being developed, which will undoubtedly increase understanding. The authors identify 'best practice' and address issues such as the importance of corporate governance, culture and ethics. Insurance as a mitigant for operational risk is also considered. Quantitative and qualitative risk assessment methodologies covered include: Loss-data analysis; extreme value theory; causal analysis including Bayesian Belief Networks; control risk self-assessment and key indicators; scenario analysis; and dynamic financial analysis. Views of industry insiders, from organisations such as Standard & Poors, Fitch, Hermes, USS, UN-PRI, Deutsche Bank, and Alchemy Partners, are presented together with those from experts at the FSA, the International Accounting Standards Board (IASB), and the Financial Reporting Council. In addition to investors, this book will be of interest to actuaries, rating agencies, regulators and legislators, as well as to the directors and risk managers of financial institutions in both the private and public sectors. Students requiring a comprehensive knowledge of operational risk management will also find the book of considerable value.

Dynamic Risk Assessment and Management of Domino Effects and Cascading Events in the Process Industry provides insights into emerging and state-of-the-art methods for the dynamic assessment of risk and safety barrier performance in the framework of domino effect risk management. The book presents methods and tools to manage the risk of cascading events involving the chemical and process industry. It is an ideal reference for both safety and security managers, industrial risk stakeholders, scientists and practitioners. In addition, laymen may find the state-of-the-art methods concerning domino effects (large-scale accidents) and how to prevent their propagation an interesting topic of study. - Includes dynamic hazard and risk assessment methods - Presents methods for safety barrier performance assessment - Addresses the effect of harsh environment on domino risk assessment - Relates physical security in relation to domino effects - Includes innovative methods and tools