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Introduction to Reliability Engineering 3rd edition [Kõva köide]

(Pratt & Whitney, Division of Raytheon Technologies, USA), (University of Hartford, USA), (Northwestern University, USA)
  • Formaat: Hardback, 640 pages, kõrgus x laius x paksus: 259x180x25 mm, kaal: 1066 g
  • Ilmumisaeg: 22-Apr-2022
  • Kirjastus: John Wiley & Sons Inc
  • ISBN-10: 1119640563
  • ISBN-13: 9781119640561
Teised raamatud teemal:
Introduction to Reliability Engineering 3rd editionSuurem pilt
  • Formaat: Hardback, 640 pages, kõrgus x laius x paksus: 259x180x25 mm, kaal: 1066 g
  • Ilmumisaeg: 22-Apr-2022
  • Kirjastus: John Wiley & Sons Inc
  • ISBN-10: 1119640563
  • ISBN-13: 9781119640561
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781119640561.html
Märksõnad:
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.

Preface xv
About the Author xix
About the Companion Website xxi
1 Introduction
1(8)
1.1 Reliability Defined
1(1)
1.2 Performance, Cost, and Reliability
2(2)
1.3 Quality, Reliability, and Safety Linkage
4(2)
1.4 Quality, Reliability, and Safety Engineering Tasks
6(1)
1.5 Preview
7(2)
Bibliography
7(2)
2 Probability and Discrete Distributions
9(38)
2.1 Introduction
9(1)
2.2 Probability Concepts
9(14)
Relative Frequency
9(1)
Classical
10(1)
Subjective
10(1)
Sample space (S) = set of all possible outcomes
10(1)
Outcome (e) = an element of the sample space
10(1)
Event = A subset of outcomes
11(1)
Probability Axioms
11(6)
More Than Two Events
17(4)
Combinations and Permutations
21(2)
2.3 Discrete Random Variables
23(24)
Properties of Discrete Variables
23(3)
The Binomial Distribution
26(4)
The Poisson Distribution
30(3)
Confidence Intervals
33(1)
Motivation for Confidence Intervals
33(2)
Introduction to Confidence Intervals
35(2)
Binomial Confidence Intervals
37(2)
Cumulative Sums of the Poisson Distribution (Thorndike Chart)
39(2)
Bibliography
41(1)
Advanced texts in Probability
41(1)
Exercises
42(5)
3 The Exponential Distribution and Reliability Basics
47(62)
3.1 Introduction
47(1)
3.2 Reliability Characterization
47(6)
Basic Definitions
48(2)
The Bathtub Curve
50(3)
3.3 Constant Failure Rate Model
53(8)
The Exponential Distribution
54(1)
Demand Failures
55(2)
Time Determinations
57(4)
3.4 Time-Dependent Failure Rates
61(2)
3.5 Component Failures and Failure Modes
63(4)
Failure Mode Rates
63(1)
Component Counts
64(3)
3.6 Replacements
67(4)
3.7 Redundancy
71(4)
Active and Standby Redundancy
72(1)
Active Parallel
72(1)
Standby Parallel
73(1)
Constant Failure Rate Models
73(2)
3.8 Redundancy Limitations
75(6)
Common-Mode Failures
76(1)
Load Sharing
77(2)
Switching and Standby Failures
79(1)
Cold, Warm, and Hot Standby
80(1)
3.9 Multiply Redundant Systems
81(5)
1/N Active Redundancy
81(2)
1/N Standby Redundancy
83(1)
m/N Active Redundancy
84(2)
3.10 Redundancy Allocation
86(8)
High- and Low-level Redundancy
88(2)
Fail Safe and Fail to Danger
90(2)
Voting Systems
92(2)
3.11 Redundancy in Complex Configurations
94(15)
Series--Parallel Configurations
94(2)
Linked Configurations
96(2)
Bibliography
98(1)
Exercises
98(5)
Redundancy
103(6)
4 Continuous Distributions -- Part 1 Normal and Related Continuous Distributions
109(40)
4.1 Introduction
109(1)
4.2 Properties of Continuous Random Variables
109(8)
Probability Distribution Functions
110(2)
Characteristics of a Probability Distribution
112(2)
Sample Statistics
114(1)
Transformations of Variables
115(2)
4.3 Empirical Cumulative Distribution Function (Empirical CDF)
117(3)
4.4 Uniform Distribution
120(2)
4.5 Normal and Related Distributions
122(13)
The Normal Distribution
123(3)
Normal Distribution Cautions and Warnings!!
126(1)
Central Limit Theorem
127(1)
Central Limit Theorem in Practice
128(1)
The Lognormal Distribution
128(6)
Log Normal Distribution from a Physics of Failure Perspective
134(1)
4.6 Confidence Intervals
135(5)
Point and Interval Estimates
135(4)
Estimate of the Mean
139(1)
4.7 Normal and Lognormal Parameters
140(9)
Bibliography
142(1)
Exercises
143(6)
5 Continuous Distributions -- Part 2 Weibull and Extreme Value Distributions
149(72)
5.1 Introduction
149(5)
The "Weakest Link" Theory from a Physics-of-Failure Point of View
149(1)
Uses of Weibull and Extreme Value Distributions
150(1)
Other Considerations
151(1)
Age Parameters and Sample Sizes
151(1)
Engineering Changes, Maintenance Plan Evaluation, and Risk Prediction
152(1)
Weibulls with Cusps or Curves
152(1)
System Weibulls
153(1)
No Failure Weibulls
154(1)
Small Sample Weibulls
154(1)
Summary
154(1)
5.2 Statistics of the Weibull Distribution
154(35)
Weibull "Mathematics"
154(4)
The Weibull Probability Plot
158(2)
Probability Plotting Points -- Median Ranks
160(1)
How to Do a "Weibull Analysis"
161(2)
Weibull Plots and Their Estimates of β, η
163(4)
The Three-Parameter Weibull Did Not Work, What Are My Choices?
167(1)
The Data has a "Dogleg" Bend or Cusp When Plotted on Weibull Paper
167(4)
Steep Weibull Slopes (βs) May Hide Problems
171(1)
Low-Time Failures and Close Serial numbers -- Batch Problems
172(1)
Maximum-Likelihood Estimates of β and η
172(4)
Weibayes Analysis
176(1)
Weibayes Background (You Do Not Necessarily Have Any Failure Times)
177(3)
Weibull Analysis with Failures Only and Unknown Times on the Unfailed Population
180(1)
Shifting Weibull Procedure
180(1)
Confidence Bounds and the Weibull Distribution
181(3)
Arbitrary Censored Data -- Left-Censored, Right-Censored, and Interval Data
184(4)
The Weibull Distribution in a System of Independent Failure Modes
188(1)
5.3 Extreme Value Distributions
189(8)
5.4 Introduction to Risk Analysis
197(24)
Risk Analysis "Mathematics"
197(6)
Bibliography
203(2)
Exercises
205(14)
Supplement 1 Weibull Derived from Weakest Link Theory
219(2)
6 Reliability Testing
221(106)
6.1 Introduction
221(2)
6.2 Attribute Testing (Binomial Testing)
223(5)
The Classical Success Run
224(1)
Zero-Failure Attribute Tests
224(1)
Non-Zero-Failure Attribute Tests
225(3)
6.3 Constant Failure Rate Estimates
228(6)
Censoring on the Right
228(2)
MTTF Estimates
230(2)
Confidence Intervals
232(2)
6.4 Weibull Substantiation and Reliability Testing
234(9)
Zero-Failure Test Plans for Substantiation Testing
235(2)
Weibull Zero-Failure Test Plans for Reliability Testing
237(2)
Reexpression of a Reliability Goal to Determine η
239(1)
Designing the Test Plan
239(2)
Test Units with Censored Times (due to Julius Wang, Fiat-Chrysler)
241(1)
Total Test Time
242(1)
Why Not Simply Test to Failure?
243(1)
6.5 How to Reduce Test Time
243(12)
Run (Simultaneously) More Test Samples Than You Intend to Fail
243(2)
Sudden Death Testing
245(2)
Sequential Testing
247(8)
6.6 Normal and Lognormal Reliability Testing
255(7)
6.7 Accelerated Life Testing
262(20)
Compressed-Time Testing
262(3)
Advanced-Stress Testing -- Linear and Acceleration Models
265(1)
Linear Model Stress Testing
266(4)
Advanced-Stress Testing -- Acceleration Models
270(1)
The Arrhenius Model
270(5)
The Inverse Power Law Model
275(5)
Other Acceleration Models
280(2)
6.8 Reliability-Enhancement Procedures
282(45)
Reliability Growth Modeling and Testing
282(5)
Calculation of Reliability Growth Parameters
287(1)
Goodness-of-Fit Tests for Reliability Growth Models
288(1)
For Time-Terminated Testing
288(1)
For Failure-Terminated Testing
289(1)
For Grouped Data
289(10)
Environmental Stress Screening
299(3)
What "Screens" are used for ESS?
302(1)
Thermal Cycling
302(1)
Random Vibration
303(1)
Other Screens
303(1)
Highly Accelerated Life Tests
304(1)
Highly Accelerated-Stress Screening
305(1)
Bibliography
305(1)
Exercises
306(9)
Supplement 1 Tables for Weibull Zero-failure Substantiatioon testing
315(4)
Supplement 2 Tables For Weibull Zer-failure Substantiation testing using (t/Eta)
319(4)
Supplement 3 Critical Values for Cramer--Von Mises Goodness-of-Fit Test
323(1)
Supplement 4 Other Reliability Growth Models that have been Proposed and Studied (see AFWAL-TR-84-2024 for details)
323(1)
(a) Deterministic Models
323(1)
(b) Poisson Process Models
324(1)
(c) Markov Processes/Time Series Models
325(1)
Supplement 5 Chi-Square Table
326(1)
7 Failure Modes and Effects Analysis -- Design and Process
327(34)
7.1 Introduction
327(1)
7.2 Functional FMEA
328(4)
7.3 Design FMEA
332(7)
Design FMEA Procedure
332(7)
7.4 Process FMEA (PFMEA)
339(10)
7.5 FMEA Summary
349(12)
Bibliography
350(1)
Exercises
350(9)
Supplement 1 Shortcut Tables for Stalled FMEA Teams
359(1)
Supplement 2 Future Changes in FMEA Approaches
360(1)
Supplement 3 DFMEA and PFMEA Forms
360(1)
8 Loads, Capacity, and Reliability
361(34)
8.1 Introduction
361(1)
8.2 Reliability with a Single Loading
362(6)
Load Application
363(1)
Definitions
364(4)
8.3 Reliability and Safety Factors
368(8)
Normal Distributions
368(5)
Lognormal Distributions
373(1)
Combined Distributions
374(2)
8.4 Repetitive Loading
376(6)
Loading Variability
376(4)
Variable Capacity
380(2)
8.5 The Bathtub Curve -- Reconsidered
382(13)
Single Failure Modes
383(2)
Combined Failure Modes
385(2)
Bibliography
387(1)
Exercises
388(4)
Supplement 1 The Dirac Delta Distribution
392(3)
9 Maintained Systems
395(32)
9.1 Introduction
395(1)
9.2 Preventive Maintenance
396(7)
Idealized Maintenance
396(5)
Imperfect Maintenance
401(2)
Redundant Components
403(1)
9.3 Corrective Maintenance
403(4)
Availability
404(1)
Maintainability
405(2)
9.4 Repair: Revealed Failures
407(4)
Constant Repair Rates
407(3)
Constant Repair Times
410(1)
9.5 Testing and Repair: Unrevealed Failures
411(4)
Idealized Periodic Tests
411(2)
Real Periodic Tests
413(2)
9.6 System Availability
415(12)
Revealed Failures
416(2)
Unrevealed Failures
418(1)
Simultaneous Testing
419(1)
Staggered Testing
420(2)
Bibliography
422(1)
Exercises
422(5)
10 Failure Interactions
427(36)
10.1 Introduction
427(1)
10.2 Markov Analysis
427(7)
Two Independent Components
429(3)
Load-Sharing Systems
432(2)
10.3 Reliability With Standby Systems
434(10)
Idealized System
434(3)
Failures in the Standby State
437(2)
Switching Failures
439(3)
Primary System Repair
442(2)
10.4 Multicomponent Systems
444(5)
Multicomponent Markov Formulations
444(4)
Combinations of Subsystems
448(1)
10.5 Availability
449(14)
Standby Redundancy
449(4)
Shared Repair Crews
453(4)
Markov Availability -- Advantages and Disadvantages
457(1)
The Advantages of Markov Availability Analysis
457(1)
The Disadvantages of Markov Availability Analysis
457(1)
Bibliography
457(1)
Exercises
457(6)
11 System Safety Analysis
463(58)
11.1 Introduction
463(1)
11.2 Product and Equipment Hazards
464(2)
11.3 Human Error
466(5)
Routine Operations
468(2)
Emergency Operations
470(1)
11.4 Methods of Analysis
471(9)
Failure Modes, Effects, and Criticality Analysis (FMECA)
472(1)
Criticality
472(6)
Event Trees
478(2)
11.5 Fault Trees
480(25)
Fault-Tree Construction
482(1)
Nomenclature
483(3)
Fault Classification
486(1)
Primary, Secondary, and Command Faults
486(1)
Passive and Active Faults
486(1)
Fault Tree Examples
487(7)
Direct Evaluation of Fault Trees
494(1)
Qualitative Evaluation
494(1)
Top Down
495(1)
Bottom Up
495(1)
Logical Reduction
496(1)
Quantitative Evaluation
496(1)
Probability Relationships
497(1)
Primary-Failure Data
498(1)
Fault-Tree Evaluation by Cut Sets
499(1)
Qualitative Analysis
499(1)
Minimum Cut-Set Formulation
499(2)
Cut-Set Determination
501(1)
Cut-Set Interpretations
502(1)
Quantitative Analysis
503(1)
Top-Event Probability
503(2)
Importance
505(1)
Uncertainty
505(1)
11.6 Reliability/Safety Risk Analysis
505(16)
Conclusion: Assuming Worst Case can be Misleading
508(1)
Another Approach: Monte Carlo Simulation
508(7)
Bibliography
515(1)
FMEA/FMECA
515(1)
Exercises
516(5)
Appendix A Useful Mathematical Relationships
521(4)
A.1 Integrals
521(1)
Definite Integrals
521(1)
Integration by Parts
521(1)
Derivative of an Integral
521(1)
A.2 Expansions
522(1)
Integer Series
522(1)
Binomial Expansion
522(1)
Geometric Progression
522(1)
Infinite Series
522(1)
A.3 Solution of First-order Linear Differential Equation
523(2)
Appendix B Binomial Failure Probability Charts
525(4)
Appendix C Φ(z): Standard Normal CDF
529(4)
Appendix D Nonparametric Methods and Probability Plotting
533(22)
D.1 Introduction
533(1)
D.2 Nonparametric Methods for Probability Plotting
533(4)
Boxplots and Histograms
533(1)
Boxplot
533(2)
Histogram
535(1)
Rank Statistics
536(1)
D.3 Parametric Methods
537(10)
Weibull Distribution Plotting
540(3)
Extreme-Value Distribution Plotting
543(2)
Lognormal Distribution Plotting
545(2)
D.4 Goodness of Fit
547(8)
Bibliography 555(2)
3rd Ed Answers to Odd -- Numbered Exercises 557(50)
Index 607
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 Universitys 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.