Introduction to Reliability Engineering

Informationen zum Autor James E. Breneman established and headed the Engineering Technical University at Pratt and Whitney, which provided more than 450,000 hours of instruction to employees during his tenure. Now retired, Breneman has taught many public course offerings for the ASQ Reliability & Risk Division. In 2018 he was awarded the Eugene L. Grant Medal for outstanding leadership in educational programs in quality. Chittaranjan Sahay holds the Vernon D. Roosa Distinguished Professor Chair in Manufacturing and Professorship in Mechanical Engineering at the University of Hartford, where he has held various offices including Associate Dean and Director of the Graduate Programs of the College of Engineering, Technology, and Architecture, and Chairman of the Mechanical Engineering Department. Elmer E. Lewis is Professor of Mechanical Engineering at Northwestern University's McCormick School of Engineering and Applied Science. He has held appointments as Visiting Professor at the University of Stuttgart and as Guest Scientist at the Nuclear Research Center at Karlsruhe, Germany. He has been a frequent consultant to Argonne and Los Alamos National Laboratories as well as a number of industrial firms. Klappentext A complete revision of the classic text on reliability engineering, written by an expanded author team with increased industry perspective Introduction to Reliability Engineering provides a thorough and well-balanced overview of the fundamental aspects of reliability engineering and describes the role of probability and statistical analysis in predicting and evaluating reliability in a range of engineering applications. Covering both foundational theory and real-world practice, this classic textbook helps students of any engineering discipline understand key probability concepts, random variables and their use in reliability, Weibull analysis, system safety analysis, reliability and environmental stress testing, redundancy, failure interactions, and more. Extensively revised to meet the needs of today's students, the Third Edition fully reflects current industrial practices and provides a wealth of new examples and problems that now require the use of statistical software for both simulation and analysis of data. A brand-new chapter examines Failure Modes and Effects Analysis (FMEA) and the Reliability Testing chapter has been greatly expanded, while new and expanded sections cover topics such as applied probability, probability plotting with software, the Monte Carlo simulation, and reliability and safety risk. Throughout the text, increased emphasis is placed on the Weibull distribution and its use in reliability engineering. Presenting students with an interdisciplinary perspective on reliability engineering, this textbook: Presents a clear and accessible introduction to reliability engineering that assumes no prior background knowledge of statistics and probability Teaches students how to solve problems involving reliability data analysis using software including Minitab and Excel Features new and updated examples, exercises, and problems sets drawn from a variety of engineering fields Includes several useful appendices, worked examples, answers to selected exercises, and a companion website Introduction to Reliability Engineering, Third Edition remains the perfect textbook for both advanced undergraduate and graduate students in all areas of engineering and manufacturing technology. Zusammenfassung Introduction to Reliability EngineeringA complete revision of the classic text on reliability engineering, written by an expanded author team with increased industry perspectiveIntroduction to Reliability Engineering provides a thorough and well-balanced overview of the fundamental aspects of reliability engineering and describes the role of probability and statistical analysis in predicting and evaluating reliabilit...

List of contents

1 INTRODUCTION
 
1.1 Reliability Defined
 
1.2 Performance, Cost and Reliability
 
1.3 Quality, Reliability and Safety Linkage
 
1.4 Quality, Reliability and Safety Engineering Tasks
 
1.5 Preview
 
2 PROBABILITY AND DISCRETE DISTRIBUTIONS
 
2.1 Introduction
 
2.2 Probability Concepts
 
Sample Space
 
Outcome
 
Event
 
Probability Axioms
 
More than two events
 
Combinations and Permutations
 
2.3 Discrete Random Variables
 
Properties of Discrete Variables
 
The Binomial Distribution
 
The Poisson Distribution
 
Confidence Intervals
 
Motivation for Confidence Intervals
 
Introduction to Confidence Intervals
 
Binomial Confidence Intervals
 
Cumulative sums of the Poisson Distribution (Thorndike Chart)
 
3 Exponential Distribution and Reliability Basics
 
3.1 Introduction
 
3.2 Reliability Characterization
 
Basic definitions
 
The Bathtub curve
 
3.3 Constant Failure Rate model
 
The Exponential Distribution
 
Demand failures
 
Time determinations
 
3.4 Time Dependent Failure rates
 
3.5 Component Failures and Failure Modes
 
Failure mode rates
 
Component counts
 
3.6 Replacements
 
3.7 Redundancy
 
Active and Standby Redundancy
 
Active Parallel
 
Standby Parallel
 
Constant Failure Rate Models
 
3.8 Redundancy limitations
 
Common-mode failures
 
Load sharing
 
Switching & Standby failures
 
Cool, Warm and Hot Standby
 
3.9 Multiply Redundant Systems
 
1/N Active Redundancy
 
1/N Standby Redundancy
 
m/N Active Redundancy
 
3.10 Redundancy Allocation
 
High and Low level redundancy
 
Fail-safe and Fail-to-Danger
 
Voting Systems
 
3.11 Redundancy in Complex Configurations
 
Serial-Parallel configurations
 
Linked configurations
 
4 Continuous Distributions- Part 1 Normal & Related Distributions
 
4.1 Introduction
 
4.2 Properties of Continuous Random variables
 
Probability Distribution Functions
 
Characteristics of a Probability Distribution
 
Sample Statistics
 
Transformation of Variables
 
4.3 Empirical Cumulative Distribution Function
 
4.4 Uniform Distribution
 
4.5 Normal and Related Distributions
 
The Normal Distribution
 
Central Limit Theorem
 
The Central Limit Theorem in Practice
 
The Log Normal Distribution
 
Log Normal Distribution from a Physics of Failure Perspective
 
4.6 Confidence Intervals
 
Point & Interval Estimates
 
Estimate of the Mean
 
Normal & Lognormal parameters
 
5 Continuous Distributions- Part 2 Weibull & Extreme Value Distributions
 
5.1 Introduction
 
The "weakest link" theory from a Physics of Failure point of view
 
Uses of Weibull and Extreme Value Distributions
 
Other Considerations
 
Age parameters and sample sizes
 
Engineering Changes, Maintenance Plan Evaluation and Risk Prediction
 
Weibulls with cusps or curves
 
System Weibulls
 
No failure Weibulls
 
Small sample Weibulls
 
5.2 Statistics of the Weibull Distribution
 
Weibull "Mathematics"
 
The Weibull Probability Plot
 
Probability Plotting Points--Median Ranks
 
How to do a "Weibull Analysis"
 
Weibull pl

Product details

• Authors: Breneman, J E Breneman, James Breneman, James E Breneman, James E. Breneman, James E. (Pratt & Whitney Breneman, Elmer Lewis, Elmer E Lewis, Elmer E. Lewis, Elmer E. Sahay Lewis, Lewis Elmer E., Chittaranjan Sahay
• Publisher: Wiley, John and Sons Ltd
• Languages: English
• Product format: Hardback
• Released: 31.12.2021
• EAN: 9781119640561
• ISBN: 978-1-119-64056-1
• No. of pages: 640
• Subjects: Natural sciences, medicine, IT, technology > Technology > Heat, energy and power station engineering; Maschinenbau, Bruchmechanik, Mechanical Engineering, Electrical & Electronics Engineering, Elektrotechnik u. Elektronik, Technische Zuverlässigkeit, Quality & Reliability, Qualität u. Zuverlässigkeit, Failure Fracture