In the industry of manufacturing and design, one major constraint has been enhancing operating performance using less time. As technology continues to advance, manufacturers are looking for better methods in predicting the condition and residual lifetime of electronic devices in order to save repair costs and their reputation. Intelligent systems are a solution for predicting the reliability of these components; however, there is a lack of research on the advancements of this smart technology within the manufacturing industry. AI Techniques for Reliability Prediction for Electronic Components provides emerging research exploring the theoretical and practical aspects of prediction methods using artificial intelligence and machine learning in the manufacturing field. Featuring coverage on a broad range of topics such as data collection, fault tolerance, and health prognostics, this book is ideally designed for reliability engineers, electronic engineers, researchers, scientists, students, and faculty members seeking current research on the advancement of reliability analysis using AI.
A high percentage of defense systems fail to meet their reliability requirements. This is a serious problem for the U.S. Department of Defense (DOD), as well as the nation. Those systems are not only less likely to successfully carry out their intended missions, but they also could endanger the lives of the operators. Furthermore, reliability failures discovered after deployment can result in costly and strategic delays and the need for expensive redesign, which often limits the tactical situations in which the system can be used. Finally, systems that fail to meet their reliability requirements are much more likely to need additional scheduled and unscheduled maintenance and to need more spare parts and possibly replacement systems, all of which can substantially increase the life-cycle costs of a system. Beginning in 2008, DOD undertook a concerted effort to raise the priority of reliability through greater use of design for reliability techniques, reliability growth testing, and formal reliability growth modeling, by both the contractors and DOD units. To this end, handbooks, guidances, and formal memoranda were revised or newly issued to reduce the frequency of reliability deficiencies for defense systems in operational testing and the effects of those deficiencies. "Reliability Growth" evaluates these recent changes and, more generally, assesses how current DOD principles and practices could be modified to increase the likelihood that defense systems will satisfy their reliability requirements. This report examines changes to the reliability requirements for proposed systems; defines modern design and testing for reliability; discusses the contractor's role in reliability testing; and summarizes the current state of formal reliability growth modeling. The recommendations of "Reliability Growth" will improve the reliability of defense systems and protect the health of the valuable personnel who operate them.
"This book explores the theoretical and practical aspects of prediction methods using artificial intelligence and machine learning in the manufacturing field"--
In modern industries, electrical energy conversion systems consist of two main parts: electrical machines and power electronic converters. With global electricity use at an all-time high, uninterrupted operation of electrical power converters is essential. Reliability in Power Electronics and Electrical Machines: Industrial Applications and Performance Models provides an in-depth analysis of reliability in electrical energy converters as well as strategies for designing dependable power electronic converters and electrical machines. Featuring a comprehensive discussion on the topics of reliability design and measurement, failure mechanisms, and specific issues pertaining to quality, efficiency, and durability, this timely reference source offers practical examples and research-based results for use by engineers, researchers, and advanced-level students.
The book charts how reliability engineering has moved from the use of sometimes arbitrary standards to an empirical scientific approach of understanding operating conditions, failure mechanisms, the need for testing for a more realistic characterisation and, new for the second edition, includes the monitoring of performance/robustness in the field. Reliability Characterisation of Electrical and Electronic Systems brings together a number of experts and key players in the discipline to concisely present the fundamentals and background to reliability theory, elaborate on the current thinking and developments behind reliability characterisation, and give a detailed account of emerging issues across a wide range of applications. The second edition has a new section titled Reliability Condition Monitoring and Prognostics for Specific Application which provides a guide to critical issues in key industrial sectors such as automotive and aerospace. There are also new chapters on areas of growing importance such as reliability methods in high-temperature electronics and reliability and testing of electric aircraft power systems. Reviews emerging areas of importance such as reliability methods in high-temperature electronics and reliability testing of electric vehicles Looks at the failure mechanisms, testing methods, failure analysis, characterisation techniques and prediction models that can be used to increase reliability Facilitates a greater understanding of operating conditions, failure mechanisms and the need for testing
The main reason for the premature breakdown of today's electronic products (computers, cars, tools, appliances, etc.) is the failure of the components used to build these products. Today professionals are looking for effective ways to minimize the degradation of electronic components to help ensure longer-lasting, more technically sound products and systems. This practical book offers engineers specific guidance on how to design more reliable components and build more reliable electronic systems. Professionals learn how to optimize a virtual component prototype, accurately monitor product reliability during the entire production process, and add the burn-in and selection procedures that are the most appropriate for the intended applications. Moreover, the book helps system designers ensure that all components are correctly applied, margins are adequate, wear-out failure modes are prevented during the expected duration of life, and system interfaces cannot lead to failure.
Drawing of real-world issues and with supporting data from industry, this book overviews the technique and equipment available to engineers and scientists to identify the solutions of the physical essence of engineering problems in simulation, accelerated testing, prediction, quality improvement, and risk during the design, manufacturing, and maintenance stages. For this goal the book integrates Quality Improvement and Accelerated Reliability/ Durability/ Maintainability/Test Engineering concepts. Accelerated Quality and Reliability Solutions includes new and unpublished aspects in quality: - complex analysis of factors that influence product quality, and other quality development and improvement problems during design and manufacturing ; in simulation: - the strategy for development of accurate physical simulation of field input influences on the actual product – a system of control for physical simulation of the random input influences – a methodology for selecting a representative input region for accurate simulation of the field conditions; in testing: - useful accelerated reliability testing (UART) – accelerated multiple environmental testing technology – trends in development of UART technology; in studying climate and reliability; in prediction: - accurate prediction (AP) of reliability, durability, and maintainability - criteria of AP - development of techniques, etc.. The book includes new and effective aspects integration of quality, reliability, and maintainability. Other key features: - Includes aspects of quality integrated with reliability which can help to solve earlier inaccessible problems during design, manufacturing, and usage - Develops a new approach to improving the engineering culture for solving quality and reliability problems. - Enables the accurate prediction of quality, reliability, durability, and maintainability - Proposes strategies for accelerated quality, reliability, durability, and maintainability improvement and development - Combines new techniques with equipment for accurate physical simulation of field situation (mechanical, electrical, multi-environmental, and other influences, as well as human and other factors) for development accelerated testing (including reliability testing) and research - Overviews the latest techniques in physical simulation; accelerated testing; prediction of reliability, durability, and maintainability; quality development and improvement; safety aspects of risk assessment, especially for transportation - Supported by real life examples and industry data - Deals with the latest techniques in physical simulation, accelerated testing, prediction of reliability, durability, maintainability, quality development and safety aspects of risk assessment - Provides step-by-step guidance on the accurate prediction of quality factors, the physical simulation of field situations and of accelerated reliability testing - Dramatically reduces recalls by solving product improvement problems through the integration of quality development with reliability
This work will educate chip and system designers on a method for accurately predicting circuit and system reliability in order to estimate failures that will occur in the field as a function of operating conditions at the chip level. This book will combine the knowledge taught in many reliability publications and illustrate how to use the knowledge presented by the semiconductor manufacturing companies in combination with the HTOL end-of-life testing that is currently performed by the chip suppliers as part of their standard qualification procedure and make accurate reliability predictions. This book will allow chip designers to predict FIT and DPPM values as a function of operating conditions and chip temperature so that users ultimately will have control of reliability in their design so the reliability and performance will be considered concurrently with their design. - The ability to include reliability calculations and test results in their product design - The ability to use reliability data provided to them by their suppliers to make meaningful reliability predictions - Have accurate failure rate calculations for calculating warrantee period replacement costs
This textbook reviews the methodologies of reliability prediction as currently used in industries such as electronics, automotive, aircraft, aerospace, off-highway, farm machinery, and others. It then discusses why these are not successful; and, presents methods developed by the authors for obtaining accurate information for successful prediction. The approach is founded on approaches that accurately duplicate the real world use of the product. Their approach is based on two fundamental components needed for successful reliability prediction; first, the methodology necessary; and, second, use of accelerated reliability and durability testing as a source of the necessary data. Applicable to all areas of engineering, this textbook details the newest techniques and tools to achieve successful reliabilityprediction and testing. It demonstrates practical examples of the implementation of the approaches described. This book is a tool for engineers, managers, researchers, in industry, teachers, and students. The reader will learn the importance of the interactions of the influencing factors and the interconnections of safety and human factors in product prediction and testing.
The main aims of power electronic converter systems (PECS) are to control, convert, and condition electrical power flow from one form to another through the use of solid state electronics. This book outlines current research into the scientific modeling, experimentation, and remedial measures for advancing the reliability, availability, system robustness, and maintainability of PECS at different levels of complexity.
