James E. Breneman, Chittaranjan Sahay, Elmer E. Lewis

Introduction to Reliability Engineering (eBook, ePUB)

• Format: ePub

Produktbeschreibung

Introduction to Reliability Engineering 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.

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Produktdetails

• Verlag: John Wiley & Sons
• Erscheinungstermin: 5. April 2022
• Englisch
• ISBN-13: 9781119640653
• Artikelnr.: 63731083

Autorenporträt

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.

Inhaltsangabe

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