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Reliability : modeling, prediction, and optimization /

Bringing together business and engineering to reliability analysis With manufactured products exploding in numbers and complexity, reliability studies play an increasingly critical role throughout a product's entire life cycle-from design to post-sale support. Reliability: Modeling, Prediction,...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Blischke, W. R., 1934-
Otros Autores: Murthy, D. N. P.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York : Wiley, ©2000.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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100 1 |a Blischke, W. R.,  |d 1934- 
245 1 0 |a Reliability :  |b modeling, prediction, and optimization /  |c by Wallace R. Blischke, D.N. Prabhakar Murthy. 
260 |a New York :  |b Wiley,  |c ©2000. 
300 |a 1 online resource (xxvii, 812 pages) :  |b illustrations 
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505 0 |a Front Matter -- Context of Reliability Analysis. An Overview -- Illustrative Cases and Data Sets -- Basic Reliability Methodology. Collection and Preliminary Analysis of Failure Data -- Probability Distributions for Modeling Time to Failure -- Basic Statistical Methods for Data Analysis -- Reliability Modeling, Estimation, and Prediction. Modeling Failures at the Component Level -- Modeling and Analysis of Multicomponent Systems -- Advanced Statistical Methods for Data Analysis -- Software Reliability -- Design of Experiments and Analysis of Variance -- Model Selection and Validation -- Reliability Management, Improvement, and Optimization. Reliability Management -- Reliability Engineering -- Reliability Prediction and Assessment -- Reliability Improvement -- Maintenance of Unreliable Systems -- Warranties and Service Contracts -- Reliability Optimization -- Epilogue. Case Studies -- Resource Materials -- Appendix A: Probability -- Appendix B: Introduction to Stochastic Processes -- Appendix C: Statistical Tables -- Appendix D: Basic Results on Stochastic Optimization -- References -- Author Index -- Subject Index -- Wiley Series in Probability and Statistics. 
504 |a Includes bibliographical references (pages 771-795) and indexes. 
505 0 0 |g Part  |t A Context of Reliability Analysis --  |g 2  |t Illustrative Cases and Data Sets  |g 31 --  |g Part B  |t Basic Reliability Methodology --  |g 3  |t Collection and Preliminary Analysis of Failure Data  |g 67 --  |g 4  |t Probability Distributions for Modeling Time to Failure  |g 93 --  |g 5  |t Basic Statistical Methods for Data Analysis  |g 135 --  |g Part C  |t Reliability Modeling, Estimation, and Prediction --  |g 6  |t Modeling Failures at the Component Level  |g 169 --  |g 7  |t Modeling and Analysis of Multicomponent Systems  |g 201 --  |g 8  |t Advanced Statistical Methods for Data Analysis  |g 243 --  |g 9  |t Software Reliability  |g 287 --  |g 10  |t Design of Experiments and Analysis of Variance  |g 319 --  |g 11  |t Model Selection and Validation  |g 375 --  |g Part D  |t Reliability Management, Improvement, and Optimization --  |g 12  |t Reliability Management  |g 427 --  |g 13  |t Reliability Engineering  |g 467 --  |g 14  |t Reliability Prediction and Assessment  |g 511 --  |g 15  |t Reliability Improvement  |g 537 --  |g 16  |t Maintenance of Unreliable Systems  |g 559 --  |g 17  |t Warranties and Service Contracts  |g 589 --  |g 18  |t Reliability Optimization  |g 619 --  |g Appendix A.  |t Probability  |g 725 --  |g A.1  |t Introduction to Probability Theory  |g 725 --  |g A.2  |t Moment-Generating and Characteristic Functions  |g 727 --  |g A.3  |t Two or More Random Variables  |g 728 --  |g A.4  |t Laplace Transforms  |g 731 --  |g A.5  |t Functions of Random Variables  |g 732 --  |g Appendix B.  |t Introduction to Stochastic Processes  |g 735 --  |g B.2  |t Markov Chains  |g 737 --  |g B.3  |t Point Processes  |g 737 --  |g B.4  |t Markov Processes  |g 746 --  |g Table C1  |t Fractiles of the Standard Normal Distribution  |g 749 --  |g Table C2  |t Fractiles of the Student-t Distribution  |g 750 --  |g Table C3  |t Fractiles of the Chi-Square Distribution  |g 752 --  |g Table C4  |t Factors for Two-Sided Tolerance Intervals, Normal Distribution  |g 752 --  |g Table C5  |t Factors for One-Sided Tolerance Intervals, Normal Distribution  |g 753 --  |g Table C6  |t Factors for Two-Sided Nonparametric Tolerance Intervals  |g 754 --  |g Table C7  |t Factors for One-Sided Nonparametric Tolerance Intervals  |g 755 --  |g Table C8  |t Fractiles of the F Distribution  |g 756 --  |g Table C9  |t Upper Percentage Points of the Studentized Range  |g 762 --  |g Appendix D.  |t Basic Results on Stochastic Optimization  |g 763 --  |g D.1  |t Unconstrained Static Optimization  |g 763 --  |g D.2  |t Constrained Static Optimization  |g 764 --  |g D.3  |t Multistage Dynamic Static Optimization  |g 766 --  |g D.4  |t Continuous Time Dynamic Optimization  |g 767. 
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520 |a Bringing together business and engineering to reliability analysis With manufactured products exploding in numbers and complexity, reliability studies play an increasingly critical role throughout a product's entire life cycle-from design to post-sale support. Reliability: Modeling, Prediction, and Optimization presents a remarkably broad framework for the analysis of the technical and commercial aspects of product reliability, integrating concepts and methodologies from such diverse areas as engineering, materials science, statistics, probability, operations research, and management. Written. 
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700 1 |a Murthy, D. N. P. 
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