Using the Weibull Distribution : Reliability, Modeling and Inference.

By: McCool, John IMaterial type: TextTextSeries: Wiley Series in Probability and Statistics SerPublisher: Somerset : John Wiley & Sons, Incorporated, 2012Copyright date: ©2012Edition: 1st edDescription: 1 online resource (368 pages)Content type: text Media type: computer Carrier type: online resourceISBN: 9781118351963Subject(s): Probabilities -- Textbooks | Weibull distribution -- TextbooksGenre/Form: Electronic books.Additional physical formats: Print version:: Using the Weibull Distribution : Reliability, Modeling and InferenceDDC classification: 519.2/4 LOC classification: QA273.6 -- .M38 2012ebOnline resources: Click to View
Contents:
Intro -- Using the Weibull Distribution -- Contents -- Preface -- CHAPTER 1: Probability -- 1.1 SAMPLE SPACES AND EVENTS -- 1.2 MUTUALLY EXCLUSIVE EVENTS -- 1.3 VENN DIAGRAMS -- 1.4 UNIONS OF EVENTS AND JOINT PROBABILITY -- 1.5 CONDITIONAL PROBABILITY -- 1.6 INDEPENDENCE -- 1.7 PARTITIONS AND THE LAW OF TOTAL PROBABILITY -- 1.8 RELIABILITY -- 1.9 SERIES SYSTEMS -- 1.10 PARALLEL SYSTEMS -- 1.11 COMPLEX SYSTEMS -- 1.12 CROSSLINKED SYSTEMS -- 1.13 RELIABILITY IMPORTANCE -- REFERENCES -- EXERCISES -- CHAPTER 2: Discrete and Continuous Random Variables -- 2.1 PROBABILITY DISTRIBUTIONS -- 2.2 FUNCTIONS OF A RANDOM VARIABLE -- 2.3 JOINTLY DISTRIBUTED DISCRETE RANDOM VARIABLES -- 2.4 CONDITIONAL EXPECTATION -- 2.5 THE BINOMIAL DISTRIBUTION -- 2.5.1 Confidence Limits for the Binomial Proportion p -- 2.6 THE POISSON DISTRIBUTION -- 2.7 THE GEOMETRIC DISTRIBUTION -- 2.8 CONTINUOUS RANDOM VARIABLES -- 2.8.1 The Hazard Function -- 2.9 JOINTLY DISTRIBUTED CONTINUOUS RANDOM VARIABLES -- 2.10 SIMULATING SAMPLES FROM CONTINUOUS DISTRIBUTIONS -- 2.11 THE NORMAL DISTRIBUTION -- 2.12 DISTRIBUTION OF THE SAMPLE MEAN -- 2.12.1 P[X < Y] for Normal Variables -- 2.13 THE LOGNORMAL DISTRIBUTION -- 2.14 SIMPLE LINEAR REGRESSION -- REFERENCES -- EXERCISES -- CHAPTER 3: Properties of the Weibull Distribution -- 3.1 THE WEIBULL CUMULATIVE DISTRIBUTION FUNCTION (CDF), PERCENTILES, MOMENTS, AND HAZARD FUNCTION -- 3.1.1 Hazard Function -- 3.1.2 The Mode -- 3.1.3 Quantiles -- 3.1.4 Moments -- 3.2 THE MINIMA OF WEIBULL SAMPLES -- 3.3 TRANSFORMATIONS -- 3.3.1 The Power Transformation -- 3.3.2 The Logarithmic Transformation -- 3.4 THE CONDITIONAL WEIBULL DISTRIBUTION -- 3.5 QUANTILES FOR ORDER STATISTICS OF A WEIBULL SAMPLE -- 3.5.1 The Weakest Link Phenomenon -- 3.6 SIMULATING WEIBULL SAMPLES -- REFERENCES -- EXERCISES -- CHAPTER 4: Weibull Probability Models.
4.1 SYSTEM RELIABILITY -- 4.1.1 Series Systems -- 4.1.2 Parallel Systems -- 4.1.3 Standby Parallel -- 4.2 WEIBULL MIXTURES -- 4.3 P(Y < X) -- 4.4 RADIAL ERROR -- 4.5 PRO RATA WARRANTY -- 4.6 OPTIMUM AGE REPLACEMENT -- 4.6.1 Age Replacement -- 4.6.2 MTTF for a Maintained System -- 4.7 RENEWAL THEORY -- 4.7.1 Block Replacement -- 4.7.2 Free Replacement Warranty -- 4.7.3 A Renewing Free Replacement Warranty -- 4.8 OPTIMUM BIDDING -- 4.9 OPTIMUM BURN-IN -- 4.10 SPARE PARTS PROVISIONING -- REFERENCES -- EXERCISES -- CHAPTER 5: Estimation in Single Samples -- 5.1 POINT AND INTERVAL ESTIMATION -- 5.2 CENSORING -- 5.3 ESTIMATION METHODS -- 5.3.1 Menon's Method -- 5.3.2 An Order Statistic Estimate of x0.10 -- 5.4 GRAPHICAL ESTIMATION OF WEIBULL PARAMETERS -- 5.4.1 Complete Samples -- 5.4.2 Graphical Estimation in Censored Samples -- 5.5 MAXIMUM LIKELIHOOD ESTIMATION -- 5.5.1 The Exponential Distribution -- 5.5.2 Confidence Intervals for the Exponential Distribution-Type II Censoring -- 5.5.3 Estimation for the Exponential Distribution-Interval Censoring -- 5.5.4 Estimation for the Exponential Distribution-Type I Censoring -- 5.5.5 Estimation for the Exponential Distribution-The Zero Failures Case -- 5.6 ML ESTIMATION FOR THE WEIBULL DISTRIBUTION -- 5.6.1 Shape Parameter Known -- 5.6.2 Confidence Interval for the Weibull Scale Parameter-Shape Parameter Known, Type II Censoring -- 5.6.3 ML Estimation for the Weibull Distribution-Shape Parameter Unknown -- 5.6.4 Confidence Intervals for Weibull Parameters-Complete and Type II Censored Samples -- 5.6.5 Interval Censoring with the Weibull -- 5.6.6 Confidence Limits for Weibull Parameters-Type I Censoring -- REFERENCES -- EXERCISES -- CHAPTER 6: Sample Size Selection, Hypothesis Testing, and Goodness of Fit -- 6.1 PRECISION MEASURE FOR MAXIMUM LIKELIHOOD (ML) ESTIMATES.
6.2 INTERVAL ESTIMATES FROM MENON'S METHOD OF ESTIMATION -- 6.3 HYPOTHESIS TESTING-SINGLE SAMPLES -- 6.4 OPERATING CHARACTERISTIC (OC) CURVES FOR ONE-SIDED TESTS OF THE WEIBULL SHAPE PARAMETER -- 6.5 OC CURVES FOR ONE-SIDED TESTS ON A WEIBULL PERCENTILE -- 6.6 GOODNESS OF FIT -- 6.6.1 Completely Specified Distribution -- 6.6.2 Distribution Parameters Not Specified -- 6.6.3 Censored Samples -- 6.6.4 The Program ADStat -- 6.7 LOGNORMAL VERSUS WEIBULL -- REFERENCES -- EXERCISES -- CHAPTER 7: The Program Pivotal.exe -- 7.1 RELATIONSHIP AMONG QUANTILES -- 7.2 SERIES SYSTEMS -- 7.3 CONFIDENCE LIMITS ON RELIABILITY -- 7.4 USING Pivotal.exe FOR OC CURVE CALCULATIONS -- 7.5 PREDICTION INTERVALS -- 7.6 SUDDEN DEATH TESTS -- 7.7 DESIGN OF OPTIMAL SUDDEN DEATH TESTS -- REFERENCES -- EXERCISES -- CHAPTER 8: Inference from Multiple Samples -- 8.1 MULTIPLE WEIBULL SAMPLES -- 8.2 TESTING THE HOMOGENEITY OF SHAPE PARAMETERS -- 8.3 ESTIMATING THE COMMON SHAPE PARAMETER -- 8.3.1 Interval Estimation of the Common Shape Parameter -- 8.4 INTERVAL ESTIMATION OF A PERCENTILE -- 8.5 TESTING WHETHER THE SCALE PARAMETERS ARE EQUAL -- 8.5.1 The SPR Test -- 8.5.2 Likelihood Ratio Test -- 8.6 MULTIPLE COMPARISON TESTS FOR DIFFERENCES IN SCALE PARAMETERS -- 8.7 AN ALTERNATIVE MULTIPLE COMPARISON TEST FOR PERCENTILES -- 8.8 THE PROGRAM MULTI-WEIBULL.EXE -- 8.9 INFERENCE ON P (Y < X) -- 8.9.1 ML Estimation -- 8.9.2 Normal Approximation -- 8.9.3 An Exact Simulation Solution -- 8.9.4 Confidence Intervals -- REFERENCES -- EXERCISES -- CHAPTER 9: Weibull Regression -- 9.1 THE POWER LAW MODEL -- 9.2 ML ESTIMATION -- 9.3 EXAMPLE -- 9.4 PIVOTAL FUNCTIONS -- 9.5 CONFIDENCE INTERVALS -- 9.6 TESTING THE POWER LAW MODEL -- 9.7 MONTE CARLO RESULTS -- 9.8 EXAMPLE CONCLUDED -- 9.9 APPROXIMATING u* AT OTHER STRESS LEVELS -- 9.10 PRECISION.
9.11 STRESS LEVELS IN DIFFERENT PROPORTIONS THAN TABULATED -- 9.12 DISCUSSION -- 9.13 THE DISK OPERATING SYSTEM (DOS) PROGRAM REGEST -- REFERENCES -- EXERCISES -- CHAPTER 10: The Three-Parameter Weibull Distribution -- 10.1 THE MODEL -- 10.2 ESTIMATION AND INFERENCE FOR THE WEIBULL LOCATION PARAMETER -- 10.3 TESTING THE TWO- VERSUS THREE-PARAMETER WEIBULL DISTRIBUTION -- 10.4 POWER OF THE TEST -- 10.5 INTERVAL ESTIMATION -- 10.6 INPUT AND OUTPUT SCREENS OF LOCEST.exe -- 10.7 THE PROGRAM LocationPivotal.exe -- 10.8 SIMULATED EXAMPLE -- REFERENCES -- EXERCISES -- CHAPTER 11: Factorial Experiments with Weibull Response -- 11.1 INTRODUCTION -- 11.2 THE MULTIPLICATIVE MODEL -- 11.3 DATA -- 11.4 ESTIMATION -- 11.5 TEST FOR THE APPROPRIATE MODEL -- 11.6 MONTE CARLO RESULTS -- 11.7 THE DOS PROGRAM TWOWAY -- 11.8 ILLUSTRATION OF THE INFLUENCE OF FACTOR EFFECTS ON THE SHAPE PARAMETER ESTIMATES -- 11.9 NUMERICAL EXAMPLES -- REFERENCES -- EXERCISES -- Index.
Summary: Understand and utilize the latest developments in Weibull inferential methods While the Weibull distribution is widely used in science and engineering, most engineers do not have the necessary statistical training to implement the methodology effectively. Using the Weibull Distribution: Reliability, Modeling, and Inference fills a gap in the current literature on the topic, introducing a self-contained presentation of the probabilistic basis for the methodology while providing powerful techniques for extracting information from data. The author explains the use of the Weibull distribution and its statistical and probabilistic basis, providing a wealth of material that is not available in the current literature. The book begins by outlining the fundamental probability and statistical concepts that serve as a foundation for subsequent topics of coverage, including: Optimum burn-in, age and block replacement, warranties and renewal theory Exact inference in Weibull regression Goodness of fit testing and distinguishing the Weibull from the lognormal Inference for the Three Parameter Weibull&#xA0; Throughout the book, a wealth of real-world examples showcases the discussed topics and each chapter concludes with a set of exercises, allowing readers to test their understanding of the presented material. In addition, a related website features the author's own software for implementing the discussed analyses along with a set of modules written in Mathcad®, and additional graphical interface software for performing simulations. With its numerous hands-on examples, exercises, and software applications, Using the Weibull Distribution is an excellent book for courses on quality control and reliability engineering at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for engineers, scientists, and business analysts whoSummary: gather and interpret data that follows the Weibull distribution.
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Intro -- Using the Weibull Distribution -- Contents -- Preface -- CHAPTER 1: Probability -- 1.1 SAMPLE SPACES AND EVENTS -- 1.2 MUTUALLY EXCLUSIVE EVENTS -- 1.3 VENN DIAGRAMS -- 1.4 UNIONS OF EVENTS AND JOINT PROBABILITY -- 1.5 CONDITIONAL PROBABILITY -- 1.6 INDEPENDENCE -- 1.7 PARTITIONS AND THE LAW OF TOTAL PROBABILITY -- 1.8 RELIABILITY -- 1.9 SERIES SYSTEMS -- 1.10 PARALLEL SYSTEMS -- 1.11 COMPLEX SYSTEMS -- 1.12 CROSSLINKED SYSTEMS -- 1.13 RELIABILITY IMPORTANCE -- REFERENCES -- EXERCISES -- CHAPTER 2: Discrete and Continuous Random Variables -- 2.1 PROBABILITY DISTRIBUTIONS -- 2.2 FUNCTIONS OF A RANDOM VARIABLE -- 2.3 JOINTLY DISTRIBUTED DISCRETE RANDOM VARIABLES -- 2.4 CONDITIONAL EXPECTATION -- 2.5 THE BINOMIAL DISTRIBUTION -- 2.5.1 Confidence Limits for the Binomial Proportion p -- 2.6 THE POISSON DISTRIBUTION -- 2.7 THE GEOMETRIC DISTRIBUTION -- 2.8 CONTINUOUS RANDOM VARIABLES -- 2.8.1 The Hazard Function -- 2.9 JOINTLY DISTRIBUTED CONTINUOUS RANDOM VARIABLES -- 2.10 SIMULATING SAMPLES FROM CONTINUOUS DISTRIBUTIONS -- 2.11 THE NORMAL DISTRIBUTION -- 2.12 DISTRIBUTION OF THE SAMPLE MEAN -- 2.12.1 P[X < Y] for Normal Variables -- 2.13 THE LOGNORMAL DISTRIBUTION -- 2.14 SIMPLE LINEAR REGRESSION -- REFERENCES -- EXERCISES -- CHAPTER 3: Properties of the Weibull Distribution -- 3.1 THE WEIBULL CUMULATIVE DISTRIBUTION FUNCTION (CDF), PERCENTILES, MOMENTS, AND HAZARD FUNCTION -- 3.1.1 Hazard Function -- 3.1.2 The Mode -- 3.1.3 Quantiles -- 3.1.4 Moments -- 3.2 THE MINIMA OF WEIBULL SAMPLES -- 3.3 TRANSFORMATIONS -- 3.3.1 The Power Transformation -- 3.3.2 The Logarithmic Transformation -- 3.4 THE CONDITIONAL WEIBULL DISTRIBUTION -- 3.5 QUANTILES FOR ORDER STATISTICS OF A WEIBULL SAMPLE -- 3.5.1 The Weakest Link Phenomenon -- 3.6 SIMULATING WEIBULL SAMPLES -- REFERENCES -- EXERCISES -- CHAPTER 4: Weibull Probability Models.

4.1 SYSTEM RELIABILITY -- 4.1.1 Series Systems -- 4.1.2 Parallel Systems -- 4.1.3 Standby Parallel -- 4.2 WEIBULL MIXTURES -- 4.3 P(Y < X) -- 4.4 RADIAL ERROR -- 4.5 PRO RATA WARRANTY -- 4.6 OPTIMUM AGE REPLACEMENT -- 4.6.1 Age Replacement -- 4.6.2 MTTF for a Maintained System -- 4.7 RENEWAL THEORY -- 4.7.1 Block Replacement -- 4.7.2 Free Replacement Warranty -- 4.7.3 A Renewing Free Replacement Warranty -- 4.8 OPTIMUM BIDDING -- 4.9 OPTIMUM BURN-IN -- 4.10 SPARE PARTS PROVISIONING -- REFERENCES -- EXERCISES -- CHAPTER 5: Estimation in Single Samples -- 5.1 POINT AND INTERVAL ESTIMATION -- 5.2 CENSORING -- 5.3 ESTIMATION METHODS -- 5.3.1 Menon's Method -- 5.3.2 An Order Statistic Estimate of x0.10 -- 5.4 GRAPHICAL ESTIMATION OF WEIBULL PARAMETERS -- 5.4.1 Complete Samples -- 5.4.2 Graphical Estimation in Censored Samples -- 5.5 MAXIMUM LIKELIHOOD ESTIMATION -- 5.5.1 The Exponential Distribution -- 5.5.2 Confidence Intervals for the Exponential Distribution-Type II Censoring -- 5.5.3 Estimation for the Exponential Distribution-Interval Censoring -- 5.5.4 Estimation for the Exponential Distribution-Type I Censoring -- 5.5.5 Estimation for the Exponential Distribution-The Zero Failures Case -- 5.6 ML ESTIMATION FOR THE WEIBULL DISTRIBUTION -- 5.6.1 Shape Parameter Known -- 5.6.2 Confidence Interval for the Weibull Scale Parameter-Shape Parameter Known, Type II Censoring -- 5.6.3 ML Estimation for the Weibull Distribution-Shape Parameter Unknown -- 5.6.4 Confidence Intervals for Weibull Parameters-Complete and Type II Censored Samples -- 5.6.5 Interval Censoring with the Weibull -- 5.6.6 Confidence Limits for Weibull Parameters-Type I Censoring -- REFERENCES -- EXERCISES -- CHAPTER 6: Sample Size Selection, Hypothesis Testing, and Goodness of Fit -- 6.1 PRECISION MEASURE FOR MAXIMUM LIKELIHOOD (ML) ESTIMATES.

6.2 INTERVAL ESTIMATES FROM MENON'S METHOD OF ESTIMATION -- 6.3 HYPOTHESIS TESTING-SINGLE SAMPLES -- 6.4 OPERATING CHARACTERISTIC (OC) CURVES FOR ONE-SIDED TESTS OF THE WEIBULL SHAPE PARAMETER -- 6.5 OC CURVES FOR ONE-SIDED TESTS ON A WEIBULL PERCENTILE -- 6.6 GOODNESS OF FIT -- 6.6.1 Completely Specified Distribution -- 6.6.2 Distribution Parameters Not Specified -- 6.6.3 Censored Samples -- 6.6.4 The Program ADStat -- 6.7 LOGNORMAL VERSUS WEIBULL -- REFERENCES -- EXERCISES -- CHAPTER 7: The Program Pivotal.exe -- 7.1 RELATIONSHIP AMONG QUANTILES -- 7.2 SERIES SYSTEMS -- 7.3 CONFIDENCE LIMITS ON RELIABILITY -- 7.4 USING Pivotal.exe FOR OC CURVE CALCULATIONS -- 7.5 PREDICTION INTERVALS -- 7.6 SUDDEN DEATH TESTS -- 7.7 DESIGN OF OPTIMAL SUDDEN DEATH TESTS -- REFERENCES -- EXERCISES -- CHAPTER 8: Inference from Multiple Samples -- 8.1 MULTIPLE WEIBULL SAMPLES -- 8.2 TESTING THE HOMOGENEITY OF SHAPE PARAMETERS -- 8.3 ESTIMATING THE COMMON SHAPE PARAMETER -- 8.3.1 Interval Estimation of the Common Shape Parameter -- 8.4 INTERVAL ESTIMATION OF A PERCENTILE -- 8.5 TESTING WHETHER THE SCALE PARAMETERS ARE EQUAL -- 8.5.1 The SPR Test -- 8.5.2 Likelihood Ratio Test -- 8.6 MULTIPLE COMPARISON TESTS FOR DIFFERENCES IN SCALE PARAMETERS -- 8.7 AN ALTERNATIVE MULTIPLE COMPARISON TEST FOR PERCENTILES -- 8.8 THE PROGRAM MULTI-WEIBULL.EXE -- 8.9 INFERENCE ON P (Y < X) -- 8.9.1 ML Estimation -- 8.9.2 Normal Approximation -- 8.9.3 An Exact Simulation Solution -- 8.9.4 Confidence Intervals -- REFERENCES -- EXERCISES -- CHAPTER 9: Weibull Regression -- 9.1 THE POWER LAW MODEL -- 9.2 ML ESTIMATION -- 9.3 EXAMPLE -- 9.4 PIVOTAL FUNCTIONS -- 9.5 CONFIDENCE INTERVALS -- 9.6 TESTING THE POWER LAW MODEL -- 9.7 MONTE CARLO RESULTS -- 9.8 EXAMPLE CONCLUDED -- 9.9 APPROXIMATING u* AT OTHER STRESS LEVELS -- 9.10 PRECISION.

9.11 STRESS LEVELS IN DIFFERENT PROPORTIONS THAN TABULATED -- 9.12 DISCUSSION -- 9.13 THE DISK OPERATING SYSTEM (DOS) PROGRAM REGEST -- REFERENCES -- EXERCISES -- CHAPTER 10: The Three-Parameter Weibull Distribution -- 10.1 THE MODEL -- 10.2 ESTIMATION AND INFERENCE FOR THE WEIBULL LOCATION PARAMETER -- 10.3 TESTING THE TWO- VERSUS THREE-PARAMETER WEIBULL DISTRIBUTION -- 10.4 POWER OF THE TEST -- 10.5 INTERVAL ESTIMATION -- 10.6 INPUT AND OUTPUT SCREENS OF LOCEST.exe -- 10.7 THE PROGRAM LocationPivotal.exe -- 10.8 SIMULATED EXAMPLE -- REFERENCES -- EXERCISES -- CHAPTER 11: Factorial Experiments with Weibull Response -- 11.1 INTRODUCTION -- 11.2 THE MULTIPLICATIVE MODEL -- 11.3 DATA -- 11.4 ESTIMATION -- 11.5 TEST FOR THE APPROPRIATE MODEL -- 11.6 MONTE CARLO RESULTS -- 11.7 THE DOS PROGRAM TWOWAY -- 11.8 ILLUSTRATION OF THE INFLUENCE OF FACTOR EFFECTS ON THE SHAPE PARAMETER ESTIMATES -- 11.9 NUMERICAL EXAMPLES -- REFERENCES -- EXERCISES -- Index.

Understand and utilize the latest developments in Weibull inferential methods While the Weibull distribution is widely used in science and engineering, most engineers do not have the necessary statistical training to implement the methodology effectively. Using the Weibull Distribution: Reliability, Modeling, and Inference fills a gap in the current literature on the topic, introducing a self-contained presentation of the probabilistic basis for the methodology while providing powerful techniques for extracting information from data. The author explains the use of the Weibull distribution and its statistical and probabilistic basis, providing a wealth of material that is not available in the current literature. The book begins by outlining the fundamental probability and statistical concepts that serve as a foundation for subsequent topics of coverage, including: Optimum burn-in, age and block replacement, warranties and renewal theory Exact inference in Weibull regression Goodness of fit testing and distinguishing the Weibull from the lognormal Inference for the Three Parameter Weibull&#xA0; Throughout the book, a wealth of real-world examples showcases the discussed topics and each chapter concludes with a set of exercises, allowing readers to test their understanding of the presented material. In addition, a related website features the author's own software for implementing the discussed analyses along with a set of modules written in Mathcad®, and additional graphical interface software for performing simulations. With its numerous hands-on examples, exercises, and software applications, Using the Weibull Distribution is an excellent book for courses on quality control and reliability engineering at the upper-undergraduate and graduate levels. The book also serves as a valuable reference for engineers, scientists, and business analysts who

gather and interpret data that follows the Weibull distribution.

Description based on publisher supplied metadata and other sources.

Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2018. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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