Design of Experiments for Reliability Achievement

ISBN-13: 9781119237693 / Angielski / Twarda / 2022 / 432 str.

Steven E. Rigdon;Rong Pan;Douglas C. Montgomery

Spis treści

Preface xiiiAbout the Companion Website xvPart I Reliability 11 Reliability Concepts 31.1 Definitions of Reliability 31.2 Concepts for Lifetimes 41.3 Censoring 102 Lifetime Distributions 172.1 The Exponential Distribution 172.2 TheWeibull Distribution 222.3 The Gamma Distribution 252.4 The Lognormal Distribution 282.5 Log Location and Scale Distributions 303 Inference for Parameters of Life Distributions 393.1 Nonparametric Estimation of the Survival Function 393.2 Maximum Likelihood Estimation 463.3 Inference for the Exponential Distribution 503.4 Inference for the Weibull 583.5 The SEV Distribution 593.6 Inference for Other Models 603.7 Bayesian Inference 67Part II Design of Experiments 894 Fundamentals of Experimental Design 914.1 Introduction to Experimental Design 914.2 A Brief History of Experimental Design 934.3 Guidelines for Designing Experiments 954.4 Introduction to Factorial Experiments 1014.5 The 2k Factorial Design 1144.6 Fractional Factorial Designs 1355 Further Principles of Experimental Design 1575.1 Introduction 1575.2 Response Surface Methods and Designs 1575.3 Optimization Techniques in Response Surface Methodology 1605.4 Designs for Fitting Response Surfaces 165Part III Regression Models for Reliability Studies 1856 Parametric Regression Models 1876.1 Introduction to Failure-Time Regression 1876.2 Regression Models with Transformations 1886.3 Generalized Linear Models 1986.4 Incorporating Censoring in Regression Models 2056.5 Weibull Regression 2086.6 Nonconstant Shape Parameter 2286.7 Exponential Regression 2336.8 The Scale-Accelerated Failure-Time Model 2346.9 Checking Model Assumptions 2367 Semi-parametric Regression Models 2497.1 The Proportional Hazards Model 2497.2 The Cox Proportional Hazards Model 2517.3 Inference for the Cox Proportional Hazards Model 2557.4 Checking Assumptions for the Cox PH Model 264Part IV Experimental Design for Reliability Studies 2698 Design of Single-Testing-Condition Reliability Experiments 2718.1 Life Testing 2728.2 Accelerated Life Testing 2869 Design of Multi-Factor and Multi-Level Reliability Experiments 2979.1 Implications of Design for Reliability 2989.2 Statistical Acceleration Models 2999.3 Planning ALTs with Multiple Stress Factors at Multiple Stress Levels 3119.4 Bayesian Design for GLM 3229.5 Reliability Experiments with Design and Manufacturing Process Variables 326Problems 336A The Survival Package in R 339B Design of Experiments using JMP 351C The Expected Fisher Information Matrix 357C.1 Lognormal Distribution 359C.2 Weibull Distribution 359C.3 Lognormal Distribution 361C.4 Weibull Distribution 362D DataSets 363E Distributions Used in Life Testing 375Bibliography 381Index 387

O autorze

Steven E. Rigdon, PhD, is Professor in the Department of Biostatistics at Saint Louis University. He is also Distinguished Research Professor Emeritus at Southern Illinois University Edwardsville. His research interests include spatial disease surveillance and reliability assessment.Rong Pan, PhD, is Associate Professor of Industrial Engineering at the School of Computing, Informatics, and Decision Systems Engineering at Arizona State University. His research interests include failure time data analysis, design of experiments, multivariate statistical quality control, time series analysis, and control.Douglas C. Montgomery, PhD, is Regents Professor of Industrial Engineering and ASU Foundation Professor of Engineering at Arizona State University. His research interests include industrial statistics and design of experiments.Laura J. Freeman, PhD, is Research Associate Professor of Statistics and Director of the Intelligent Systems Division of the National Security Institute at Virginia Tech. Her research interests include design of experiments, leveraging experimental methods in emerging technology research with a focus in cyber-physical systems, artificial intelligence (AI), and machine learning.