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Statistical reliability engineering ...

Pham, Hoang.

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Statistical reliability engineering = methods, models and applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Statistical reliability engineering/ by Hoang Pham.
Reminder of title:	methods, models and applications /
Author:	Pham, Hoang.
Published:	Cham :Springer International Publishing : : 2022.,
Description:	xx, 497 p. :ill., digital ;24 cm.
[NT 15003449]:	Probability, Statistics, and Reliability Concepts -- Distribution Functions and Its Applications -- Statistical Parameter Estimation -- System Reliability Modeling -- Order Statistics and Reliability Estimation -- Stochastic Processes -- Maintenance Modeling -- Software Reliability -- Statistical Machine Learning Methods and Its Applications.
Contained By:	Springer Nature eBook
Subject:	Reliability (Engineering) - Statistical methods. -
Online resource:	https://doi.org/10.1007/978-3-030-76904-8
ISBN:	9783030769048

Statistical reliability engineering = methods, models and applications /
Pham, Hoang.

Statistical reliability engineeringmethods, models and applications /[electronic resource] :by Hoang Pham. - Cham :Springer International Publishing :2022. - xx, 497 p. :ill., digital ;24 cm. - Springer series in reliability engineering,2196-999X. - Springer series in reliability engineering..

Probability, Statistics, and Reliability Concepts -- Distribution Functions and Its Applications -- Statistical Parameter Estimation -- System Reliability Modeling -- Order Statistics and Reliability Estimation -- Stochastic Processes -- Maintenance Modeling -- Software Reliability -- Statistical Machine Learning Methods and Its Applications.

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.

ISBN: 9783030769048

Standard No.: 10.1007/978-3-030-76904-8doiSubjects--Topical Terms:

646295
Reliability (Engineering)
--Statistical methods.

LC Class. No.: TA169 / .P43 2022

Dewey Class. No.: 620.00452

Statistical reliability engineering = methods, models and applications /
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505 0 $a Probability, Statistics, and Reliability Concepts -- Distribution Functions and Its Applications -- Statistical Parameter Estimation -- System Reliability Modeling -- Order Statistics and Reliability Estimation -- Stochastic Processes -- Maintenance Modeling -- Software Reliability -- Statistical Machine Learning Methods and Its Applications.
520 $a 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.
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