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Probability Theory In Engineering
pdf | 8.45 MB | English | Isbn:978-1119373520 |
Author: bmr | PAge: 446 | Year: 2020
Description:
Handbook and reference for industrial statisticians and system reliability engineers
System Reliability Theory: Models, Statistical Methods, and Applications, Third Edition presents an updated and revised look at system reliability theory, modeling, and analytical methods. The new edition is based on feedback to the second edition from numerous students, professors, researchers, and industries around the world. New sections and chapters are added together with new real-world industry examples, and standards and problems are revised and updated.
System Reliability Theory covers a broad and deep array of system reliability topics, including:
· In depth discussion of failures and failure modes
· The main system reliability assessment methods
· Common-cause failure modeling
· Deterioration modeling
· Maintenance modeling and assessment using Python code
· Bayesian probability and methods
· Life data analysis using R
Perfect for undergraduate and graduate students taking courses in reliability engineering, this book also serves as a reference and resource for practicing statisticians and engineers.
Throughout, the book has a practical focus, incorporating industry feedback and real-world industry problems and examples.
System Reliability Theory: Models, Statistical Methods, and Applications, Third Edition presents an updated and revised look at system reliability theory, modeling, and analytical methods. The new edition is based on feedback to the second edition from numerous students, professors, researchers, and industries around the world. New sections and chapters are added together with new real-world industry examples, and standards and problems are revised and updated.
System Reliability Theory covers a broad and deep array of system reliability topics, including:
· In depth discussion of failures and failure modes
· The main system reliability assessment methods
· Common-cause failure modeling
· Deterioration modeling
· Maintenance modeling and assessment using Python code
· Bayesian probability and methods
· Life data analysis using R
Perfect for undergraduate and graduate students taking courses in reliability engineering, this book also serves as a reference and resource for practicing statisticians and engineers.
Throughout, the book has a practical focus, incorporating industry feedback and real-world industry problems and examples.
Category:Industrial Quality Control, Textbooks
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