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The Reliability Data Handbook

The Reliability Data Handbook
Author: T. R. Moss
Publisher:
Total Pages: 287
Release: 2005
Genre: Materials
ISBN: 9780791802335

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The Reliability Data Handbook

The Reliability Data Handbook
Author: T. R. Moss
Publisher: Professional Engineering Publishing
Total Pages: 320
Release: 2004
Genre: Technology & Engineering
ISBN:

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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.


Human Reliability and Safety Analysis Data Handbook

Human Reliability and Safety Analysis Data Handbook
Author: David I. Gertman
Publisher: John Wiley & Sons
Total Pages: 480
Release: 1993-12-16
Genre: Technology & Engineering
ISBN: 9780471591108

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Takes into account the human element as well as the classical aspects of mechanical, electrical and chemical designs that contribute to risk. Features a significant amount of data essential for risk analysis not normally available. Contains numerous examples of authentic applications and case studies.


Guidelines for Process Equipment Reliability Data, with Data Tables

Guidelines for Process Equipment Reliability Data, with Data Tables
Author: CCPS (Center for Chemical Process Safety)
Publisher: John Wiley & Sons
Total Pages: 326
Release: 2010-09-16
Genre: Technology & Engineering
ISBN: 047093834X

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The book supplements Guidelines for Chemical Process Quantitative Risk Analysis by providing the failure rate data needed to perform a chemical process quantitative risk analysis.


OREDA

OREDA
Author: OREDA.
Publisher:
Total Pages:
Release: 2009
Genre: Offshore oil industry
ISBN: 9788214048315

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Reliability and Life Testing Handbook

Reliability and Life Testing Handbook
Author: Dimitri Kececioglu
Publisher: DEStech Publications, Inc
Total Pages: 910
Release: 2002
Genre: Technology & Engineering
ISBN: 9781932078039

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Includes the binomial tests of comparison and information on Accept-Reject Tests, the Sequential Probability Ratio Test, Bayesian MTBF and Reliability Demonstration Tests, as well as other important accelerated tests such as Arrhenius, Eyriing, Bazovsky, and Inverse Power Law.


Statistical Methods for Reliability Data

Statistical Methods for Reliability Data
Author: William Q. Meeker
Publisher: John Wiley & Sons
Total Pages: 708
Release: 2022-01-24
Genre: Technology & Engineering
ISBN: 1118594487

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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 Analysis

Reliability Data Collection and Analysis
Author: J. Flamm
Publisher: Springer Science & Business Media
Total Pages: 323
Release: 2012-12-06
Genre: Technology & Engineering
ISBN: 9401124388

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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.