Probabilistic Prognostics and Health Management of Energy Systems


Book Description

This book proposes the formulation of an efficient methodology that estimates energy system uncertainty and predicts Remaining Useful Life (RUL) accurately with significantly reduced RUL prediction uncertainty. Renewable and non-renewable sources of energy are being used to supply the demands of societies worldwide. These sources are mainly thermo-chemo-electro-mechanical systems that are subject to uncertainty in future loading conditions, material properties, process noise, and other design parameters.It book informs the reader of existing and new ideas that will be implemented in RUL prediction of energy systems in the future. The book provides case studies, illustrations, graphs, and charts. Its chapters consider engineering, reliability, prognostics and health management, probabilistic multibody dynamical analysis, peridynamic and finite-element modelling, computer science, and mathematics.




From Prognostics and Health Systems Management to Predictive Maintenance 1


Book Description

This book addresses the steps needed to monitor health assessment systems and the anticipation of their failures: choice and location of sensors, data acquisition and processing, health assessment and prediction of the duration of residual useful life. The digital revolution and mechatronics foreshadowed the advent of the 4.0 industry where equipment has the ability to communicate. The ubiquity of sensors (300,000 sensors in the new generations of aircraft) produces a flood of data requiring us to give meaning to information and leads to the need for efficient processing and a relevant interpretation. The process of traceability and capitalization of data is a key element in the context of the evolution of the maintenance towards predictive strategies.




Diagnostics and Prognostics of Engineering Systems: Methods and Techniques


Book Description

Industrial Prognostics predicts an industrial system’s lifespan using probability measurements to determine the way a machine operates. Prognostics are essential in determining being able to predict and stop failures before they occur. Therefore the development of dependable prognostic procedures for engineering systems is important to increase the system’s performance and reliability. Diagnostics and Prognostics of Engineering Systems: Methods and Techniques provides widespread coverage and discussions on the methods and techniques of diagnosis and prognosis systems. Including practical examples to display the method’s effectiveness in real-world applications as well as the latest trends and research, this reference source aims to introduce fundamental theory and practice for system diagnosis and prognosis.




Data-Driven Technology for Engineering Systems Health Management


Book Description

This book introduces condition-based maintenance (CBM)/data-driven prognostics and health management (PHM) in detail, first explaining the PHM design approach from a systems engineering perspective, then summarizing and elaborating on the data-driven methodology for feature construction, as well as feature-based fault diagnosis and prognosis. The book includes a wealth of illustrations and tables to help explain the algorithms, as well as practical examples showing how to use this tool to solve situations for which analytic solutions are poorly suited. It equips readers to apply the concepts discussed in order to analyze and solve a variety of problems in PHM system design, feature construction, fault diagnosis and prognosis.




Prognostics


Book Description

Prognostics is the science of making predictions of engineering systems. It is part of a suite of techniques that determine whether a system is behaving within nominal operational performance and - if it does not - that determine what is wrong and how long it will take until the system no longer fulfills certain functional requirements. This book presents the latest developments and research findings on the topic of prognostics by the Prognostics Center of Excellence at NASA Ames Research Center. The book is intended to provide a practitioner with an understanding of the foundational concepts as well as practical tools to perform prognostics and health management on different types of engineering systems and in particular to predict remaining useful life.




Computational Methods for Reliability and Risk Analysis


Book Description

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.




Digital Twin Driven Smart Manufacturing


Book Description

Digital Twin Driven Smart Manufacturing examines the background, latest research, and application models for digital twin technology, and shows how it can be central to a smart manufacturing process.The interest in digital twin in manufacturing is driven by a need for excellent product reliability, and an overall trend towards intelligent, and connected manufacturing systems. This book provides an ideal entry point to this subject for readers in industry and academia, as it answers the questions: (a) What is a digital twin? (b) How to construct a digital twin? (c) How to use a digital twin to improve manufacturing efficiency? (d) What are the essential activities in the implementation of a digital twin? (e) What are the most important obstacles to overcome for the successful deployment of a digital twin? (f) What are the relations between digital twin and New Technologies? (g) How to combine digital twin with the New Technologies to achieve high efficiency and smartness in manufacturing?This book focuses on these problems as it aims to help readers make the best use of digital twin technology towards smart manufacturing. - Analyzes the differences, synergies and possibilities for integration between digital twin technology and other technologies, such as big data, service and Internet of Things - Discuss new requirements for a traditional three-dimension digital twin and proposes a methodology for a five-dimension version - Investigates new models for optimized manufacturing, prognostics and health management, and cyber-physical fusion based on the digital twin




System Health Management


Book Description

System Health Management: with Aerospace Applications provides the first complete reference text for System Health Management (SHM), the set of technologies and processes used to improve system dependability. Edited by a team of engineers and consultants with SHM design, development, and research experience from NASA, industry, and academia, each heading up sections in their own areas of expertise and co-coordinating contributions from leading experts, the book collates together in one text the state-of-the-art in SHM research, technology, and applications. It has been written primarily as a reference text for practitioners, for those in related disciplines, and for graduate students in aerospace or systems engineering. There are many technologies involved in SHM and no single person can be an expert in all aspects of the discipline.System Health Management: with Aerospace Applications provides an introduction to the major technologies, issues, and references in these disparate but related SHM areas. Since SHM has evolved most rapidly in aerospace, the various applications described in this book are taken primarily from the aerospace industry. However, the theories, techniques, and technologies discussed are applicable to many engineering disciplines and application areas. Readers will find sections on the basic theories and concepts of SHM, how it is applied in the system life cycle (architecture, design, verification and validation, etc.), the most important methods used (reliability, quality assurance, diagnostics, prognostics, etc.), and how SHM is applied in operations (commercial aircraft, launch operations, logistics, etc.), to subsystems (electrical power, structures, flight controls, etc.) and to system applications (robotic spacecraft, tactical missiles, rotorcraft, etc.).




Population Health Management


Book Description

“This is an outstanding book and I would highly recommend it for any professional or faculty in a current public health role, and absolutely for a student in the fields of public health, nursing, health administration, health education, medicine, and information technology (artificial intelligence)... This book provides the resources for professionals to learn and apply theory, analytics, quality, and services to understand populations with the ultimate goal of transforming U.S. health care." ---Doody's Review Service, 5 stars Population Health Management: Strategies, Tools, Applications, and Outcomes uniquely combines perspectives and concepts from community, public, and global health and aligns them with the essentials of health management. Written by leading experts in academia and industry, this text emphasizes the integration of management skills necessary to deliver quality care while producing successful outcomes sensitive to the needs of diverse populations. Designed to be both student-friendly and comprehensive, this text utilizes various models, frameworks, case examples, chapter podcasts, and more to illustrate foundational knowledge and impart the skills necessary for health care managers to succeed throughout the health care sector. The book spans core topics such as community needs assessments, social determinants of health, the role of data analytics, managerial epidemiology, value-based care payment models, and new population health delivery models. COVID-19 examples throughout chapters illustrate population health management strategies solving real-world challenges. Practical and outcomes-driven, Population Health Management prepares students in health administration and management, public health, social work, allied health, and other health professions for the challenges of an evolving health care ecosystem and the changing roles in the health management workforce. Key Features: Highlights up-to-date topics focusing on social marketing, design thinking for innovation, adopting virtual care and telehealth strategies, and social marketing ideas Introduces new population health management skills and tools such as the Social Vulnerability Index, Policy Map, PRAPARE, the PHM Framework, Design Thinking and Digital Messaging Incorporates "Did You Know?" callouts, chapter-based podcasts, and discussion questions to help explain real-world situations and examples that students and health professionals may encounter as administrators and managers Includes four full-length case studies focusing on the co-production of health, implementing a population health data analytics platform, health equity, and collaborative leadership Connects chapter objectives with the National Center for Healthcare Leadership (NCHL) and the Public Health Foundation (PHF) competencies Purchase includes digital access for use on most mobile devices or computers, as well as full suite of instructor resources with Instructor's Manual, PowerPoint slides, test bank, and sample syllabus




Risk-Based Engineering


Book Description

The book comprehensively covers the various aspects of risk modeling and analysis in technological contexts. It pursues a systems approach to modeling risk and reliability concerns in engineering, and covers the key concepts of risk analysis and mathematical tools used to assess and account for risk in engineering problems. The relevance of incorporating risk-based structures in design and operations is also stressed, with special emphasis on the human factor and behavioral risks. The book uses the nuclear plant, an extremely complex and high-precision engineering environment, as an example to develop the concepts discussed. The core mechanical, electronic and physical aspects of such a complex system offer an excellent platform for analyzing and creating risk-based models. The book also provides real-time case studies in a separate section to demonstrate the use of this approach. There are many limitations when it comes to applications of risk-based approaches to engineering problems. The book is structured and written in a way that addresses these key gap areas to help optimize the overall methodology. This book serves as a textbook for graduate and advanced undergraduate courses on risk and reliability in engineering. It can also be used outside the classroom for professional development courses aimed at practicing engineers or as an introduction to risk-based engineering for professionals, researchers, and students interested in the field.