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El. knyga: Reliability Analysis and Prediction with Warranty Data: Issues, Strategies, and Methods [Taylor & Francis e-book]

(University of Massachusetts, North Dartmouth, USA), (Consultant, MI, USA)
  • Formatas: 184 pages, 22 Tables, black and white; 71 Illustrations, black and white
  • Išleidimo metai: 28-Apr-2009
  • Leidėjas: CRC Press Inc
  • ISBN-13: 9780429191022
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  • Taylor & Francis e-book
  • Kaina: 147,72 €*
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  • Standartinė kaina: 211,02 €
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Reliability Analysis and Prediction with Warranty Data: Issues, Strategies, and MethodsDidesnis paveikslėlis
  • Formatas: 184 pages, 22 Tables, black and white; 71 Illustrations, black and white
  • Išleidimo metai: 28-Apr-2009
  • Leidėjas: CRC Press Inc
  • ISBN-13: 9780429191022
Kitos knygos pagal šią temą:
Taylor & Francis e-booksMore info about Taylor & Francis e-books
Partnerių interneto svetainė: https://www.taylorfrancis.com/books/9780429191022
Rai (business statistics, Wayne State University) and Singh (Rapid Global Business Solutions) present methods for arriving at hazard rate estimates when mileage accumulation rates in the vehicle population are available in the case of hard failures, estimating hazard function when mileage accumulation rate is not available, and addressing bias in warranty data due to customer-rush near the warranty expiration limit. Intended for industrial engineers and Six Sigma black belts, the last two chapters provide a methodology for assessing the impact of changes in warranty period and describe the application of neural networks to forecast warranty performance in the presence of warranty growth phenomena. Annotation ©2009 Book News, Inc., Portland, OR (booknews.com)

Through simple, practical approaches, Reliability Analysis and Prediction with Warranty Data: Issues, Strategies, and Methods helps Six Sigma black belts and engineers successfully interpret warranty data to make accurate predictions. It discusses how to use this data to define and analyze field problems, provides guidelines for discovering the root causes for warranty cost reduction, and explores issues associated with warranty data and the approaches to overcome them.

The first part of the book presents an introduction to reliability analysis and prediction using warranty data and highlights the issues involved. The second section offers strategies and methods for obtaining component-level nonparametric hazard rate estimates that provide important clues toward probable root causes and that help reduce warranty costs. Focusing on the prediction of warranty performance, the final part deals with methodologies that assess the impact of changes in warranty limits and forecast warranty performance.

This user-friendly book shows how warranty data can support various levels of decision making to achieve reliable outcomes. Easily understood even for those with minimal statistical background, it includes objectives and summaries in each chapter to enable quick review of the topics.

List of Figures ix
List of Tables xiii
Notation xv
Acronyms xvii
Preface xix
Acknowledgments xxi
The Authors xxiii
SECTION I Need for Analysis and Prediction with Warranty Data, and Issues Involved
Chapter 1 Reliability Studies with Warranty Data: Need and Issues
3
Objectives
3
Overview
3
1.1 Continuous Improvement and Field Data
3
1.2 Three Levels Of Decision Making with Warranty Data
5
1.3 The Role of Hazard Function in Reliability and Robustness Improvements
7
1.4 Warranty Data: Not Always Perfect for Statistical Analysis
9
1.5 Existing Research Work and Certain Limitations
13
1.6 The Scope and Objective of the Book
14
1.7 Warranty Concepts
15
1.7.1 One- and Two-Dimensional Warranty Coverage
15
1.7.2 Base and Extended Warranty
16
1.7.3 Failure Modes, Causes, and Severity
16
1.7.4 Role of Warranty
17
1.7.5 Important Functions in Reliability Studies from Warranty Data
17
1.7.6 Six Sigma and Warranty Data
17
1.8 Organization of the Book
19
Bibliographic Notes
20
Chapter 2 Characterization of Warranty Data
21
Objectives
21
Overview
21
2.1 Life Cycle of a Vehicle
21
2.2 An Overview of the Warranty Claim Process
23
2.3 Automobile Warranty Data: Key Characteristics
24
2.4 Two Inherent Characteristics of Warranty Data: Uncleanliness and Incompleteness
27
2.4.1 Unclean Warranty Data
27
2.4.1.1 Type of Failure Mode
27
2.4.1.2 Service Quality
29
2.4.1.3 Unintended Data Entry Errors
29
2.4.2 Incompleteness of Warranty Data
29
2.4.2.1 Truncated Warranty Data
29
2.4.2.2 Censored Warranty Data
30
2.4.2.3 Missing Warranty Data
31
2.5 Summary
31
SECTION II Strategies and Methods for Reliability Analysis with Warranty Data
Chapter 3 Strategies for Reliability Analysis from Warranty Data
35
Objectives
35
Overview
35
3.1 From Customer Concerns to Root Causes
35
3.2 Strategies for Hazard Function Estimation
38
3.3 Summary
41
Chapter 4 Hard Failures with Known Mileage Accumulation Rates
43
Objectives
43
Overview
43
4.1 Risk Set Adjustment in Hazard Function
43
4.2 Modeling of Mileage Accumulation Rate in the Vehicle Population
44
4.3 A Four-Step Methodology
47
4.4 An Application Example
48
4.5 Summary
49
Chapter 5 Hard Failures with Unknown Mileage Accumulation Rates
53
Objectives
53
Overview
53
5.1 Hazard Function with Modification in Numerator
53
5.2 Modeling Mileage on Failed Vehicles Using Truncated Normal Distribution
54
5.2.1 Methods to Estimate Population Parameters of a Truncated Normal Distribution
56
5.2.2 A Study of Factors Affecting the Estimation Process
57
5.3 A Five-Step Methodology
61
5.4 An Application Example
63
5.5 Summary
65
Bibliographic Notes
69
Chapter 6 Soft Failures with Known Mileage Accumulation Rates
71
Objectives
71
Overview
71
6.1 Introduction
72
6.2 Risk Set Adjustment: MIS as Life Variable
73
6.3 Risk Set Adjustment: Mileage as Life Variable
74
6.4 Incorporating Censoring Information in the Hazard Function Estimation
76
6.4.1 Nonparametric MLE of Hazard Function
76
6.4.2 Variance–Covariance Matrix for the Maximum Likelihood Estimates
78
6.5 A Six-Step Methodology
80
6.6 An Application Example
81
6.6.1 The Six Steps
81
6.6.2 Comments on Results
83
6.7 Summary
88
Bibliographic Notes
88
Chapter 7 Soft Failures with Unknown Mileage Accumulation Rates
89
Objectives
89
Overview
89
7.1 Hazard Function
90
7.2 Estimation from Doubly Truncated Data Sets
91
7.2.1 Use of a Special Chart and Table to Obtain MLEs
93
7.2.2 Maximum Likelihood Estimate Using an Iterative Procedure
96
7.2.3 Covariance Matrix of the Maximum Likelihood Estimator
97
7.3 Incorporating Censoring Information in the Hazard Function Estimation
97
7.4 A Seven-Step Methodology
98
7.5 An Application Example
100
7.6 Summary
105
SECTION III Warranty Prediction
Chapter 8 Assessing the Impact of New Time/Mileage Warranty Limits
109
Objectives
109
Overview
109
8.1 Changes in the Warranty Coverage
109
8.2 The Estimation of Number of Warranty Claims
110
8.2.1 The Choice of a Data Set
111
8.2.2 Modeling of the First Failures
111
8.2.3 Repeat Failures
112
8.2.4 Claims per Thousand
114
8.2.5 Application Example 1
115
8.3 Cost of Warranty Claims
118
8.3.1 The Effect of Failure Nature and Time of Occurrence on Warranty Cost
118
8.3.2 The Effect of Mileage Accumulation Rate on Warranty Cost
120
8.3.3 Application Example 2
121
8.4 Summary
123
Bibliographic Notes
124
Chapter 9 Forecasting of Automobile Warranty Performance
125
Objectives
125
Overview
125
9.1 Warranty Growth or Maturing Data Phenomena
125
9.2 Current Warranty Forecasting Methods
128
9.3 Warranty Performance Forecasting Using RBF Neural Networks
130
9.3.1 Network Structure
130
9.3.2 Training the RBF Network
132
9.3.3 Optimization of RBF Network Structure through Experimentation
133
9.4 Forecasting Warranty Performance Using MLP Neural Networks
137
9.4.1 Net work Structure
137
9.4.2 Optimization of MLP Network Using Response Surface Methodology
138
9.5 Results and Discussions
141
9.6 Summary
147
Bibliographic Notes
147
References 149
Index 155
Bharatendra K. Rai is an assistant professor in the Charlton College of Business at the University of Massachusetts, North Dartmouth. An ASQ Six Sigma black belt, Dr. Rai has a vast amount of consulting and training experiences in the automotive, electronics, food, pharmaceutical, software, chemical, and defense industries.

Nanua Singh is the president of Rapid Global Business Solutions, Inc., Madison Heights, Michigan. Dr. Singh was previously a professor at the India Institute of Technology, Delhi; head of the Department of Industrial Engineering at the University of Windsor, Canada; and professor of manufacturing engineering at Wayne State University, Detroit, Michigan.
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