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Author: Pierre Dersin Publisher: ISBN: 9781032168647 Category : Reliability (Engineering) Languages : en Pages : 0
Book Description
"Modeling Remaining Useful Life Dynamics in Reliability Engineering applies traditional reliability engineering methods to Prognostics and Health Management (PHM), looking at Remaining Useful Life (RUL) and predictive maintenance to enable engineers to effectively and safely predict machinery lifespan. One of the key tools used in defining and implementing predictive maintenance policies is the RUL indicator. However, it is essential to account for the uncertainty inherent to the RUL, as otherwise predictive maintenance strategies can be incorrect. This can cause high costs, or alternatively, ineffective predictions. Methods used to estimate RUL are very numerous and diverse, and broadly speaking, fall into three categories: model-based, data-driven, or hybrid, which uses both. The book starts by building on established theory, and applying cutting edge research to it, such as artificial intelligence models and deep learning. It looks at traditional reliability engineering methods through their relation to Prognostics and Health Management (PHM) requirements and presents the concept of RUL loss rate. Following on from this, the book presents a general method for defining a nonlinear transformation enabling the MRL to become a linear function. It also touches on topics such as Weibull distribution, gamma distribution and degradation, along with time-to-failure distributions. Features: Provides both practical and theoretical background of RUL. Describes how the uncertainty of RUL can be related to RUL loss rate. Provides new insights into time-to-failure distributions. Offers tools for predictive maintenance. The book will be of interest to engineers and researchers in reliability engineering, Prognostics and Health Management and industry management"--
Author: Pierre Dersin Publisher: ISBN: 9781032168647 Category : Reliability (Engineering) Languages : en Pages : 0
Book Description
"Modeling Remaining Useful Life Dynamics in Reliability Engineering applies traditional reliability engineering methods to Prognostics and Health Management (PHM), looking at Remaining Useful Life (RUL) and predictive maintenance to enable engineers to effectively and safely predict machinery lifespan. One of the key tools used in defining and implementing predictive maintenance policies is the RUL indicator. However, it is essential to account for the uncertainty inherent to the RUL, as otherwise predictive maintenance strategies can be incorrect. This can cause high costs, or alternatively, ineffective predictions. Methods used to estimate RUL are very numerous and diverse, and broadly speaking, fall into three categories: model-based, data-driven, or hybrid, which uses both. The book starts by building on established theory, and applying cutting edge research to it, such as artificial intelligence models and deep learning. It looks at traditional reliability engineering methods through their relation to Prognostics and Health Management (PHM) requirements and presents the concept of RUL loss rate. Following on from this, the book presents a general method for defining a nonlinear transformation enabling the MRL to become a linear function. It also touches on topics such as Weibull distribution, gamma distribution and degradation, along with time-to-failure distributions. Features: Provides both practical and theoretical background of RUL. Describes how the uncertainty of RUL can be related to RUL loss rate. Provides new insights into time-to-failure distributions. Offers tools for predictive maintenance. The book will be of interest to engineers and researchers in reliability engineering, Prognostics and Health Management and industry management"--
Author: Pierre Dersin Publisher: CRC Press ISBN: 1000886905 Category : Technology & Engineering Languages : en Pages : 452
Book Description
This book applies traditional reliability engineering methods to prognostics and health management (PHM), looking at remaining useful life (RUL) and its dynamics, to enable engineers to effectively and accurately predict machinery and systems useful lifespan. One of the key tools used in defining and implementing predictive maintenance policies is the RUL indicator. However, it is essential to account for the uncertainty inherent to the RUL, as otherwise predictive maintenance strategies can be incorrect. This can cause high costs or, alternatively, inappropriate decisions. Methods used to estimate RUL are numerous and diverse and, broadly speaking, fall into three categories: model-based, data-driven, or hybrid, which uses both. The author starts by building on established theory and looks at traditional reliability engineering methods through their relation to PHM requirements and presents the concept of RUL loss rate. Following on from this, the author presents an innovative general method for defining a nonlinear transformation enabling the mean residual life to become a linear function of time. He applies this method to frequently encountered time-to-failure distributions, such as Weibull and gamma, and degradation processes. Latest research results, including the author’s (some of which were previously unpublished), are drawn upon and combined with very classical work. Statistical estimation techniques are then presented to estimate RUL from field data, and risk-based methods for maintenance optimization are described, including the use of RUL dynamics for predictive maintenance. The book ends with suggestions for future research, including links with machine learning and deep learning. The theory is illustrated by industrial examples. Each chapter is followed by a series of exercises. FEATURES Provides both practical and theoretical background of RUL Describes how the uncertainty of RUL can be related to RUL loss rate Provides new insights into time-to-failure distributions Offers tools for predictive maintenance This book will be of interest to engineers, researchers and students in reliability engineering, prognostics and health management, and maintenance management.
Author: Prabhakar V. Varde Publisher: Springer Nature ISBN: 9819991226 Category : Technology & Engineering Languages : en Pages : 173
Book Description
This book presents the latest research in the areas of development and application of risk-informed and risk-based technologies. The book discusses how advances in computational technologies, availability of accumulated experience and data on design, operations, maintenance and regulations, new insights in human factor modelling and development of new technologies, such as physics-of-failure modelling, prognostics and health management, have paved the way for implementation of risk and reliability tools and methods. The book will be useful for researchers, academicians, and engineers, particularly the field engineers, designers and regulators working on complex engineering systems.
Author: Jan Awrejcewicz Publisher: L& H Scientific Publishing ISBN: Category : Science Languages : en Pages : 106
Book Description
Vibration Testing and System Dynamics is an interdisciplinary journal serving as the forum for promoting dialogues among engineering practitioners and research scholars. As the platform for facilitating the synergy of system dynamics, testing, design, modeling, and education, the journal publishes high-quality, original articles in the theory and applications of dynamical system testing. The aim of the journal is to stimulate more research interest in and attention for the interaction of theory, design, and application in dynamic testing. Manuscripts reporting novel methodology design for modelling and testing complex dynamical systems with nonlinearity are solicited. Papers on applying modern theory of dynamics to real-world issues in all areas of physical science and description of numerical investigation are equally encouraged. Progress made in the following topics are of interest, but not limited, to the journal: Vibration testing and designDynamical systems and controlTesting instrumentation and controlComplex system dynamics in engineeringDynamic failure and fatigue theoryChemical dynamics and bio-systemsFluid dynamics and combustionPattern dynamicsNetwork dynamicsPlasma physics and plasma dynamicsControl signal synchronization and trackingBio-mechanical systems and devicesStructural and multi-body dynamicsFlow or heat-induced vibrationMass and energy transfer dynamicsWave propagation and testing
Author: Diego Galar Publisher: CRC Press ISBN: 1000518264 Category : Technology & Engineering Languages : en Pages : 491
Book Description
Maintenance combines various methods, tools, and techniques in a bid to reduce maintenance costs while increasing the reliability, availability, and security of equipment. Condition-based maintenance (CBM) is one such method, and prognostics forms a key element of a CBM program based on mathematical models for predicting remaining useful life (RUL). Prognostics and Remaining Useful Life (RUL) Estimation: Predicting with Confidence compares the techniques and models used to estimate the RUL of different assets, including a review of the relevant literature on prognostic techniques and their use in the industrial field. This book describes different approaches and prognosis methods for different assets backed up by appropriate case studies. FEATURES Presents a compendium of RUL estimation methods and technologies used in predictive maintenance Describes different approaches and prognosis methods for different assets Includes a comprehensive compilation of methods from model-based and data-driven to hybrid Discusses the benchmarking of RUL estimation methods according to accuracy and uncertainty, depending on the target application, the type of asset, and the forecast performance expected Contains a toolset of methods and a way of deployment aimed at a versatile audience This book is aimed at professionals, senior undergraduates, and graduate students in all interdisciplinary engineering streams that focus on prognosis and maintenance.
Author: Jingshan Li Publisher: John Wiley & Sons ISBN: 1119060877 Category : Technology & Engineering Languages : en Pages : 412
Book Description
Addresses the methodology and theoretical foundation of battery manufacturing, service and management systems (BM2S2), and discusses the issues and challenges in these areas This book brings together experts in the field to highlight the cutting edge research advances in BM2S2 and to promote an innovative integrated research framework responding to the challenges. There are three major parts included in this book: manufacturing, service, and management. The first part focuses on battery manufacturing systems, including modeling, analysis, design and control, as well as economic and risk analyses. The second part focuses on information technology’s impact on service systems, such as data-driven reliability modeling, failure prognosis, and service decision making methodologies for battery services. The third part addresses battery management systems (BMS) for control and optimization of battery cells, operations, and hybrid storage systems to ensure overall performance and safety, as well as EV management. The contributors consist of experts from universities, industry research centers, and government agency. In addition, this book: Provides comprehensive overviews of lithium-ion battery and battery electrical vehicle manufacturing, as well as economic returns and government support Introduces integrated models for quality propagation and productivity improvement, as well as indicators for bottleneck identification and mitigation in battery manufacturing Covers models and diagnosis algorithms for battery SOC and SOH estimation, data-driven prognosis algorithms for predicting the remaining useful life (RUL) of battery SOC and SOH Presents mathematical models and novel structure of battery equalizers in battery management systems (BMS) Reviews the state of the art of battery, supercapacitor, and battery-supercapacitor hybrid energy storage systems (HESSs) for advanced electric vehicle applications Advances in Battery Manufacturing, Services, and Management Systems is written for researchers and engineers working on battery manufacturing, service, operations, logistics, and management. It can also serve as a reference for senior undergraduate and graduate students interested in BM2S2.
Author: Stephen Ekwaro-Osire Publisher: Springer ISBN: 3319558528 Category : Technology & Engineering Languages : en Pages : 273
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.
Author: Henk C. Tijms Publisher: John Wiley and Sons ISBN: 0470864281 Category : Mathematics Languages : en Pages : 448
Book Description
The field of applied probability has changed profoundly in the past twenty years. The development of computational methods has greatly contributed to a better understanding of the theory. A First Course in Stochastic Models provides a self-contained introduction to the theory and applications of stochastic models. Emphasis is placed on establishing the theoretical foundations of the subject, thereby providing a framework in which the applications can be understood. Without this solid basis in theory no applications can be solved. Provides an introduction to the use of stochastic models through an integrated presentation of theory, algorithms and applications. Incorporates recent developments in computational probability. Includes a wide range of examples that illustrate the models and make the methods of solution clear. Features an abundance of motivating exercises that help the student learn how to apply the theory. Accessible to anyone with a basic knowledge of probability. A First Course in Stochastic Models is suitable for senior undergraduate and graduate students from computer science, engineering, statistics, operations resear ch, and any other discipline where stochastic modelling takes place. It stands out amongst other textbooks on the subject because of its integrated presentation of theory, algorithms and applications.
Author: Pierre Dersin
Author: Pierre Dersin
Author: Pierre Dersin
Author: Prabhakar V. Varde
Author: Jan Awrejcewicz
Author: Diego Galar
Author: Jingshan Li
Author: Stephen Ekwaro-Osire
Author: Kim Phuc Tran
Author: Henk C. Tijms
Author: