Last edited by Mezishicage

Tuesday, April 28, 2020 | History

5 edition of **Statistical and Probabilistic Models in Reliability (Statistics for Industry and Technology)** found in the catalog.

- 148 Want to read
- 30 Currently reading

Published
**December 1, 1998** by Birkhäuser Boston .

Written in English

- Mathematics for scientists & engineers,
- Technology: General Issues,
- Science/Mathematics,
- Probabilities,
- Engineering Statistics,
- Reliability Engineering,
- Technology,
- Mathematics,
- Reliability (Engineering),
- Probability & Statistics - General,
- Applied,
- Mathematics / Applied,
- Mathematics / Statistics,
- Mathematics-Probability & Statistics - General,
- Statistaical methods,
- Quality Control,
- Mathematical models

**Edition Notes**

Contributions | Nikolaos Limnios (Editor), Dumitru Cezar Ionescu (Editor) |

The Physical Object | |
---|---|

Format | Hardcover |

Number of Pages | 396 |

ID Numbers | |

Open Library | OL8074630M |

ISBN 10 | 0817640681 |

ISBN 10 | 9780817640682 |

Probabilistic Reliability Models is an excellent book for statistics, engineering, and operations. research courses on applied probability at the upper-undergraduate and graduate levels. The. book is also a valuable reference for professionals and researchers working in industry who.

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Reliability: Probabilistic Models and Statistical Methods 2nd ed. Edition by Lawrence Mark Leemis (Author) out of 5 stars 4 ratings. ISBN ISBN Why is ISBN important. ISBN. This bar-code number lets you verify that you're getting exactly the right version or edition of a book.

Cited by: This is the first of two books on the statistical theory of reliability and life testing. The present book concentrates on probabilistic aspects of reliability theory, while the forthcoming book will focus on inferential aspects of reliability and life testing, applying the probabilistic tools developed in this volume.

This book emphasizes the newer, research aspects of reliability theory. The papers have been divided into three sections: statistical methods, probabilistic methods, and special techniques and appli cations.

Of course, as with any classification, some papers could be as well assigned to other sections. Problems in reliability are. An elementary introduction to the probabilistic models and statistical methods used by reliability engineers as applied to, for example, electrical or mechanical systems.

Leemis offers explanations of how the mathematical models and results apply to engineering design and the analysis of lifetime data sets, with simple, supplementary proofs and /5(3). Applied Reliability Engineering and Risk Analysis is one of the first works to treat the important areas of degradation analysis, multi-state system reliability, networks and large-scale systems in one comprehensive volume.

It is an essential reference for engineers and scientists involved in reliability analysis, applied probability and. Offers an introduction to the probabilistic models and statistical methods used by reliability engineers as applied to electrical or mechanical systems.

This text offers explanations of how mathematical models and results apply to engineering design and the analysis of lifetime data sets, with simple, supplementary proofs and derivations provided/5(3). : System Reliability Theory: Models, Statistical Methods, and Applications, 2nd Edition (Wiley Series in Probability and Statistics) ( Cited by: The groundwater drought risk (GDR), reliability, and resistance indices were obtained by probabilistic models for the representative wells in Sina basin.

The GDR results show that the entire Sina basin is affected by mild and moderate droughts and that more localized severe drought is observed in northern region of the Sina basin. Statistical modeling and analysis of repairable systems / Bo Henry Lindqvist --CPIT goodness-of-fit tests for reliability growth models / Olivier Gaudoin --On the use of minimally informative copulae in competing risk problems / Tim Bedford --Model building in accelerated experiments / V.

Bagdonavicius and M.S. Nikulin --On semiparametric. Abstract: This is the first of two books on the statistical theory of reliability and life testing. The present book concentrates on probabilistic aspects of reliability theory, while the forthcoming book will focus on inferential aspects of reliability and life testing, applying the probabilistic tools developed in this volume.

This book emphasizes the newer, research aspects of reliability. Probabilistic Reliability Models is an excellent book for statistics, engineering, and operations.

research courses on applied probability at the upper-undergraduate and graduate levels. The. book is also a valuable reference for professionals and researchers working in. Get this from a library. Statistical and Probabilistic Models in Reliability. [D C Ionescu; N Limnios] -- This volume consists of twenty-four papers selected by the editors from the sixty-one papers presented at the 1st International Conference on Mathemati.

Reliability theory is a branch of applied mathematics with so many clear applications in engineering, manufacturing, and business. Understanding structure functions, probabilistic ways to represent item lifetimes, accelerated life testing, and repairable systems aids in better system design, warranties, and decision making about maintenance and repair.

Reliability analysis is concerned with the analysis of devices and systems whose individual components are prone to failure. This textbook presents an introduction to reliability analysis of repairable and non-repairable systems.

It is based on courses given to Brand: Springer-Verlag New York. This complete resource on the theory and applications of reliability engineering, probabilistic models and risk analysis consolidates all the latest research, presenting the most up-to-date developments in this comprehensive coverage of the theoretical and practical issues of both classic and modern topics, it also provides a unique commemoration to the centennial of.

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This site is. "The book discusses reliability engineering with a combination of statistical rigor and good readability. It covers both reliability models and analysis of failure data. The text is well organized and methodological and contains examples and exercises as well. (source: Nielsen Book Data) Summary Appropriate for a one-semester advanced undergraduate or a graduate level course in reliability engineering.

An elementary introduction to the probabilistic models and statistical methods used by reliability engineers as applied to, for example, electrical or mechanical systems. -- Probabilistic models for the reliability of repairable systems -- Statistical methods, including graphical methods, for analyzing data from repairable systems.

The first part of this book looks much like a book on stochastic processes, although. a Mahmoodian, in Reliability and Maintainability of In-Service Pipelines, Probabilistic Modes.

Probabilistic models are often used when historical failure or inspection data is limited or unavailable. These models specifically analyze the effective parameters on pipe performance rather than evaluating the previous pipe failure history.

Offers an introduction to the probabilistic models and statistical methods used by reliability engineers as applied to electrical or mechanical systems. This text offers explanations of how mathematical models and results apply to engineering design and the analysis of lifetime data sets, with simple, supplementary proofs and derivations provided.

Appropriate for a one-semester advanced undergraduate or a graduate level course in reliability engineering. An elementary introduction to the probabilistic models and statistical methods used by reliability engineers as applied to, for example, electrical or mechanical systems.

Leemis offers explanations of how the mathematical models and results apply to engineering design and the. COUPON: Rent Reliability Probabilistic Models and Statistical Methods 2nd edition () and save up to 80% on textbook rentals and 90% on used textbooks.

Get FREE 7-day instant eTextbook access. An elementary introduction to the probabilistic models and statistical methods used by reliability engineers as applied to, for example, electrical or mechanical systems.

Leemis offers explanations of how the mathematical models and results apply to engineering design and the analysis of lifetime data sets, with simple, supplementary proofs and Brand: Ascended Ideas. Home Browse by Title Books Reliability: probabilistic models and statistical methods.

Reliability: probabilistic models and statistical methods March March Read More. Author: Lawrence M. Leemis. College of William and Mary, Williamsburg, VA. Publisher: Prentice-Hall, Inc.

This book provides an up-to-date survey of new models and methods for reliability analysis and their applications in science, engineering, and technology. Inhalt. Statistical methods; probabilistic methods; special techniques and Edition: This is the first of two books on the statistical theory of reliability and life testing.

The present book concentrates on probabilistic aspects of reliability theory, while the forthcoming book Author: Donald R. Smith. Probabilistic models for the failure of materials are a first step towards reliability models that account for different scales of defects present in materials.

This paper stresses the following points developped during this session: the description and simulation of the microstructure, the Statistical analysis of mechanical data, models of Author: D. Jeulin, P. Rossi. Statistical modelling (or “data science” or “machine learning”, to use related and more trendy terms) is an important part of risk analysis and safety in various engineering areas (mechanical engineering, nuclear engineering), in the management.

This is the first of two books on the statistical theory of reliability and life testing. The present book concentrates on probabilistic aspects of reliability theory, while the forthcoming book will focus on inferential aspects of reliability and life testing, applying the probabilistic tools developed in this volume.

This book emphasizes the newer, research aspects of reliability by: (). Reliability: Probabilistic Models and Statistical Metbods. Technometrics: Vol. 38, No. 3, pp. Cited by: Category: Mathematics Applied Reliability Engineering and Risk Analysis: Probabilistic Models and Statistical Inference free ebook download.

The argument is made that probability models provide an effective vehicle for portraying and evaluating the variability that is inherent in the performance and longevity of equipment. With a blend of mathematical rigor and readability, this book is the ideal introductory textbook for graduate students and a useful resource for practising engineers.

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We also offer variant types and type of the e-books to search. Presenting an integrated approach to reliability evaluation and maintenance planning, "Reliability Engineering: Probabilistic Models and Maintenance Methods" provides comprehensive coverage of the fundamental concepts of reliability theory, basic models, and various methods of contains numerous examples and homework problems in each.

is predicted using reliability of similar parts, where failure rates are adjusted for the oper ating environment, geometry, material change, etc. Physics-based techniques: Reliability is predicted using probabilistic engineering models expressed as loads and environment vs.

capabilityFile Size: KB. Probabilistic Reliability Models eBook: Ushakov, Igor A.: : Kindle Store. Skip to main content. Try Prime Hello. Sign in Account & Lists Account & Lists Returns & Orders Try Prime Cart.

Kindle Store. Go Search Hello Select your Author: Igor A. Ushakov. Reliability engineering is a sub-discipline of systems engineering that emphasizes dependability in the lifecycle management of a ility describes the ability of a system or component to function under stated conditions for a specified period of time.

Reliability is closely related to availability, which is typically described as the ability of a component or system to function at. To know the difference between probabilistic and deterministic model we should know about what is models, or more specifically what is a mathematical model.

At the outset, we should be precisely able to differentiate between an observable phenomen. Book Descriptions: An elementary introduction to the probabilistic models and statistical methods used by reliability engineers as applied to, for example, electrical or mechanical systems.

Leemis offers explanations of how the mathematical models and results apply to engineering design and the analysis of lifetime data sets, with simple, supplementary proofs and derivations provided. Presenting an integrated approach to reliability evaluation and maintenance planning, Reliability Engineering: Probabilistic Models and Maintenance Methods provides comprehensive coverage of the fundamental concepts of reliability theory, basic models, and various methods of analysis.

It contains numerous examples and homework problems in each Cited by: A statistical model is a mathematical model that embodies a set of statistical assumptions concerning the generation of sample data (and similar data from a larger population).A statistical model represents, often in considerably idealized form, the data-generating process.

A statistical model is usually specified as a mathematical relationship between one or more random .Probabilistic Reliability Models eBook: Ushakov, Igor A.: : Kindle Store. Skip to main Try Prime EN Hello, Sign in Account & Lists Sign in Account & Lists Returns & Orders Try Prime Cart. Kindle Store.

Go Search Hello Select your address Author: Igor A. Ushakov.