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Informationen zum Autor D. N. PRABHAKAR MURTHY, PhD, is a Professor of Engineering andOperations Management at the University of Queensland in Brisbane,Australia. He received his PhD in applied mathematics from HarvardUniversity. MIN XIE, PhD, is an Associate Professor of Industrial andSystems Engineering at the National University of Singapore in KentRidge Crescent, Singapore. He received his PhD in qualitytechnology from Linkoping University in Linkoping, Sweden. RENYAN JIANG, PhD, is a Professor of Engineering at the ChangshaUniversity of Science and Technology and is also affiliated withthe Department of Mechanical Industrial Engineering at theUniversity of Toronto in Toronto, Ontario, Canada. He received hisPhD in mechanical engineering from the University ofQueensland. Klappentext A comprehensive perspective on Weibull models The literature on Weibull models is vast, disjointed, and scattered across many different journals. Weibull Models is a comprehensive guide that integrates all the different facets of Weibull models in a single volume. This book will be of great help to practitioners in reliability and other disciplines in the context of modeling data sets using Weibull models. For researchers interested in these modeling techniques, exercises at the end of each chapter define potential topics for future research. Organized into seven distinct parts, Weibull Models: Covers model analysis, parameter estimation, model validation, and application Serves as both a handbook and a research monograph. As a handbook, it classifies the different models and presents their properties. As a research monograph, it unifies the literature and presents the results in an integrated manner Intertwines theory and application Focuses on model identification prior to model parameter estimation Discusses the usefulness of the Weibull Probability plot (WPP) in the model selection to model a given data set Highlights the use of Weibull models in reliability theory Filled with in-depth analysis, Weibull Models pulls together the most relevant information on this topic to give everyone from reliability engineers to applied statisticians involved with reliability and survival analysis a clear look at what Weibull models can offer. Zusammenfassung Covers model analysis! parameter estimation! model validation! and application. This work also classifies the different models and their properties; intertwines theory and application; and focuses on model identification prior to model parameter estimation. Inhaltsverzeichnis Preface xiii PART A OVERVIEW 1 Chapter 1 Overview 3 1.1 Introduction 3 1.2 Illustrative Problems 5 1.3 Empirical Modeling Methodology 7 1.4 Weibull Models 9 1.5 Weibull Model Selection 11 1.6 Applications of Weibull Models 12 1.7 Outline of the Book 15 1.8 Notes 16 Exercises 16 Chapter 2 Taxonomy for Weibull Models 18 2.1 Introduction 18 2.2 Taxonomy for Weibull Models 18 2.3 Type I Models: Transformation of Weibull Variable 21 2.4 Type II Models: Modification/Generalization of Weibull Distribution 23 2.5 Type III Models: Models Involving Two or More Distributions 28 2.6 Type IV Models: Weibull Models with Varying Parameters 30 2.7 Type V Models: Discrete Weibull Models 33 2.8 Type VI Models: Multivariate Weibull Models 34 2.9 Type VII Models: Stochastic Point Process Models 37 Exercises 39 PART B BASIC WEIBULL MODEL 43 Chapter 3 Model Analysis 45 3.1 Introduction 45 3.2 Basic Concepts 45 3.3 Standard Weibull Model 50 3.4 Three-Parameter Weibull Model 54 3.5 Notes 55 Exercises 56 Chapter 4 Parameter Estimation 58 4.1 Introduction 58 4.2 Data Types 58
