Reliability Engineering For Industrial Processes

This reference text introduces advanced topics in the field of reliability engineering, introduces statistical modeling techniques, and probabilistic methods for diverse applications. It comprehensively covers important topics including consecutive-type reliability systems, coherent structures, multi-scale statistical modeling, the performance of reliability structures, big data analytics, prognostics, and health management. It covers real-life applications including optimization of telecommunication networks, complex infrared detecting systems, oil pipeline systems, and vacuum systems in accelerators or spacecraft relay stations. The text will serve as an ideal reference book for graduate students and academic researchers in the fields of industrial engineering, manufacturing science, mathematics, and statistics.

Over the last 50 years, the theory and the methods of reliability analysis have developed significantly. Therefore, it is very important to the reliability specialist to be informed of each reliability measure. This book will provide historical developments, current advancements, applications, numerous examples, and many case studies to bring the reader up-to-date with the advancements in this area. It covers reliability engineering in different branches, includes applications to reliability engineering practice, provides numerous examples to illustrate the theoretical results, and offers case studies along with real-world examples. This book is useful to engineering students, research scientist, and practitioners working in the field of reliability.

This book presents the state-of-the-art methodology and detailed analytical models and methods used to assess the reliability of complex systems and related applications in statistical reliability engineering. It is a textbook based mainly on the author’s recent research and publications as well as experience of over 30 years in this field. The book covers a wide range of methods and models in reliability, and their applications, including: statistical methods and model selection for machine learning; models for maintenance and software reliability; statistical reliability estimation of complex systems; and statistical reliability analysis of k out of n systems, standby systems and repairable systems. Offering numerous examples and solved problems within each chapter, this comprehensive text provides an introduction to reliability engineering graduate students, a reference for data scientists and reliability engineers, and a thorough guide for researchers and instructors in the field.

This reference text introduces advanced topics in the field of reliability engineering, introduces statistical modeling techniques, and probabilistic methods for diverse applications. It comprehensively covers important topics including consecutive-type reliability systems, coherent structures, multi-scale statistical modeling, the performance of reliability structures, big data analytics, prognostics, and health management. It covers real-life applications including optimization of telecommunication networks, complex infrared detecting systems, oil pipeline systems, and vacuum systems in accelerators or spacecraft relay stations. The text will serve as an ideal reference book for graduate students and academic researchers in the fields of industrial engineering, manufacturing science, mathematics, and statistics.

Human reliability is an issue that is increasingly discussed in the process and manufacturing industries to check factors that influence operator performance and trigger errors. Human Factor and Reliability Analysis to Prevent Losses in Industrial Processes: An Operational Culture Perspective provides a multidisciplinary analysis of work concepts and environments to reduce human error and prevent material, energy, image, and time losses. The book presents a methodology for the quantification and investigation of human reliability, and verification of the influence of human factors in the generation of process losses, consisting of the following steps: contextualization, data collection, and results; performing task and loss observation; socio-technical variable analyses; and data processing. Investigating human reliability, concepts, and models in situations of human error in practice, the book identifies where low reliability occurs and then visualizes where and how to perform an intervention. This guide is an excellent resource for professionals in chemical, petrochemical, oil, and nuclear industries for managing and analyzing safety and loss risks and for students in chemical and process engineering. Relates human reliability to the environment, leadership, decision models, possible mistakes and successes, mental map constructions, and organizational cultures Provides techniques for the diagnosis of human and operational reliability Gives examples of the application of methodologies in the stage of diagnosis and program construction Discusses competences for the analysis of process losses in industry Investigates real-life situations where human errors cause losses Includes practical examples and case studies

This book shows how to build in and assess reliability, availability, maintainability, and safety (RAMS) of components, equipment, and systems. It presents the state of the art of reliability (RAMS) engineering, in theory & practice, and is based on over 30 years author's experience in this field, half in industry and half as Professor of Reliability Engineering at the ETH, Zurich. The book structure allows rapid access to practical results. Methods & tools are given in a way that they can be tailored to cover different RAMS requirement levels. Thanks to Appendices A6 - A8 the book is mathematically self-contained, and can be used as a textbook or as a desktop reference with a large number of tables (60), figures (210), and examples / exercises^ 10,000 per year since 2013) were the motivation for this final edition, the 13th since 1985, including German editions. Extended and carefully reviewed to improve accuracy, it represents the continuous improvement effort to satisfy reader's needs and confidence. New are an introduction to risk management with structurally new models based on semi-Markov processes & to the concept of mean time to accident, reliability & availability of a k-out-of-n redundancy with arbitrary repair rate for n - k=2, 10 new homework problems, and refinements, in particular, on multiple failure mechanisms, approximate expressions, incomplete coverage, data analysis, and comments on ë, MTBF, MTTF, MTTR, R, PA.

Recent Advances in System Reliability Engineering describes and evaluates the latest tools, techniques, strategies, and methods in this topic for a variety of applications. Special emphasis is put on simulation and modelling technology which is growing in influence in industry, and presents challenges as well as opportunities to reliability and systems engineers. Several manufacturing engineering applications are addressed, making this a particularly valuable reference for readers in that sector. Contains comprehensive discussions on state-of-the-art tools, techniques, and strategies from industry Connects the latest academic research to applications in industry including system reliability, safety assessment, and preventive maintenance Gives an in-depth analysis of the benefits and applications of modelling and simulation to reliability