The ever increasing public demand and the setting-up of national and international legislation on safety assessment of potentially dangerous plants require that a correspondingly increased effort be devoted by regulatory bodies and industrial organisations to collect reliability data in order to produce safety analyses. Reliability data are also needed to assess availability of plants and services and to improve quality of production processes, in particular, to meet the needs of plant operators and/or designers regarding maintenance planning, production availability, etc. The need for an educational effort in the field of data acquisition and processing has been stressed within the framework of EuReDatA, an association of organisations operating reliability data banks. This association aims to promote data exchange and pooling of data between organisations and to encourage the adoption of compatible standards and basic definitions for a consistent exchange of reliability data. Such basic definitions are considered to be essential in order to improve data quality. To cover issues directly linked to the above areas ample space is devoted to the definition of failure events, common cause and human error data, feedback of operational and disturbance data, event data analysis, lifetime distributions, cumulative distribution functions, density functions, Bayesian inference methods, multivariate analysis, fuzzy sets and possibility theory, etc.

Warranty Data Collection and Analysis deals with warranty data collection and analysis and the problems associated with these activities. The book is a both a research monograph and a handbook for practitioners. As a research monograph, it unifies the literature on warranty data collection and analysis, and presents the important results in an integrated manner. In the process, it highlights topics that require further research. As a handbook, it provides the essential methodology needed by practitioners involved with warranty data collection and analysis, along with extensive references to further results. Models and techniques needed for proper and effective analysis of data are included, together with guidelines for their use in warranty management, product improvement, and new product development. Warranty Data Collection and Analysis will be of interest to researchers (engineers and statisticians) and practitioners (engineers, applied statisticians, and managers) involved with product warranty and reliability. It is also suitable for use as a reference text for graduate-level reliability programs in engineering, applied statistics, operations research, and management.

An authoritative guide to the most recent advances in statistical methods for quantifying reliability Statistical Methods for Reliability Data, Second Edition (SMRD2) is an essential guide to the most widely used and recently developed statistical methods for reliability data analysis and reliability test planning. Written by three experts in the area, SMRD2 updates and extends the long- established statistical techniques and shows how to apply powerful graphical, numerical, and simulation-based methods to a range of applications in reliability. SMRD2 is a comprehensive resource that describes maximum likelihood and Bayesian methods for solving practical problems that arise in product reliability and similar areas of application. SMRD2 illustrates methods with numerous applications and all the data sets are available on the book’s website. Also, SMRD2 contains an extensive collection of exercises that will enhance its use as a course textbook. The SMRD2's website contains valuable resources, including R packages, Stan model codes, presentation slides, technical notes, information about commercial software for reliability data analysis, and csv files for the 93 data sets used in the book's examples and exercises. The importance of statistical methods in the area of engineering reliability continues to grow and SMRD2 offers an updated guide for, exploring, modeling, and drawing conclusions from reliability data. SMRD2 features: Contains a wealth of information on modern methods and techniques for reliability data analysis Offers discussions on the practical problem-solving power of various Bayesian inference methods Provides examples of Bayesian data analysis performed using the R interface to the Stan system based on Stan models that are available on the book's website Includes helpful technical-problem and data-analysis exercise sets at the end of every chapter Presents illustrative computer graphics that highlight data, results of analyses, and technical concepts Written for engineers and statisticians in industry and academia, Statistical Methods for Reliability Data, Second Edition offers an authoritative guide to this important topic.

Reliability data collection and its use in risk and availability assessment is a subject of increasing importance. The founders of EuReDatA, and in particular, Arne Ullman, the originator 'and first Chairman of the Association, recognised the need for a body capable of acting as a catalyst and providing a unified approach to this subject. It is therefore a prevailing objective of the European Reliability Databank Association to initiate and support contact between experts, companies and institutions active in reliability engineering and research. Although the first and principle interest of EuReDatA is reliability data and data banks, the Association is aware that these are tools that are used with others to establish and maintain reliability and safety. It is with this objective that EuReDatA regularly holds conferences and seminars covering a range of reliability topics. C.A. Campbell H.J. Wingender EuReDatA Chairman Organiser, Editor Contents CHAPTER 1: OVERVIEWS Data Situation and the Quality of Risk Assessment (FRG) A. Birkhofer, K. Koberlein (GRS) ..••••....•.•...••.....•.•.. 3 Reliability Engineering in Europe (CEC) G. Volta (JRC-Ispra) •...••••... •...........•••.•....•.••..••. 16 1984: A Year of Industrial Catastrophies.

Written for those who have taken a first course in statistical methods, this book takes a modern, computer-oriented approach to describe the statistical techniques used for the assessment of reliability.

Component failure rate data are a vital part of any reliability or safety study and highly relevant to the engineering community across many disciplines. This book gives a comprehensive account of the subject.

This book provides, as simply as possible, sound foundations for an in-depth understanding of reliability engineering with regard to qualitative analysis, modelling, and probabilistic calculations of safety and production systems. Drawing on the authors’ extensive experience within the field of reliability engineering, it addresses and discusses a variety of topics, including: • Background and overview of safety and dependability studies; • Explanation and critical analysis of definitions related to core concepts; • Risk identification through qualitative approaches (preliminary hazard analysis, HAZOP, FMECA, etc.); • Modelling of industrial systems through static (fault tree, reliability block diagram), sequential (cause-consequence diagrams, event trees, LOPA, bowtie), and dynamic (Markov graphs, Petri nets) approaches; • Probabilistic calculations through state-of-the-art analytical or Monte Carlo simulation techniques; • Analysis, modelling, and calculations of common cause failure and uncertainties; • Linkages and combinations between the various modelling and calculation approaches; • Reliability data collection and standardization. The book features illustrations, explanations, examples, and exercises to help readers gain a detailed understanding of the topic and implement it into their own work. Further, it analyses the production availability of production systems and the functional safety of safety systems (SIL calculations), showcasing specific applications of the general theory discussed. Given its scope, this book is a valuable resource for engineers, software designers, standard developers, professors, and students.