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E-raamat: Achieving Product Reliability: A Key to Business Success

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Are you buying a car or smartphone or dishwasher? We bet long-term, trouble-free operation (i.e., high reliability) is among the top three things you look for. Reliability problems can lead to everything from minor inconveniences to human disasters. Ensuring high reliability in designing and building manufactured products is principally an engineering challenge–but statistics plays a key role.

Achieving Product Reliability

explains in a non-technical manner

how statistics is used in modern product reliability assurance.

Features:

  • Describes applications of statistics in reliability assurance in design, development, validation, manufacturing, and field tracking.
  • Uses real-life examples to illustrate key statistical concepts such as the Weibull and lognormal distributions, hazard rate, and censored data.
  • Demonstrates the use of graphical tools in such areas as accelerated testing, degradation data modeling, and repairable systems data analysis.
  • Presents opportunities for profitably applying statistics in the era of Big Data and Industrial Internet of Things (IIoT) utilizing, for example, the instantaneous transmission of large quantities of field data.

Whether you are an intellectually curious citizen, student, manager, budding reliability professional, or academician seeking practical applications, Achieving Product Reliability is a great starting point for a big-picture view of statistics in reliability assurance.

The authors are world-renowned experts on this topic with extensive experience as company-wide statistical resources for a global conglomerate, consultants to business and government, and researchers of statistical methods for reliability applications.

Arvustused

"The person reading this book will need to have an elementary understanding of statistics.These chapters focuses on the future of reliability and how this will impact us all in the various industries. Machine learning will also play a big part in the future of industries; this also is mentioned. For anyone studying a reliability field, this book is a must. A+"(Jacque van der Westhuizen, RAM Specialist-Sasol)

"Engineers and managers working in industries that utilize reliability methods on a regular basis should find this book useful. These chapters explain the "what and why" for applying reliability methods to real problems. The text is extremely clear, especially for such a technical topic. It is written for non-specialists, and is well-written for this audienceI would recommend publication, because I found this to be unique material, which would be of significant practical usefulness. Further, each of the authors is well-known in the field, adding further credibility to the work." (Roger Hoerl, Union College)

"The book will be of interest to academics and practitioners alike. For academics the book provides a broader range of applications of statistics in practice and industry. The way the authors discussed the examples are pitched at the right level for post-graduate engineering students to understand the importance of statistical thinking in reliability studies, and also for statistics students to provide an understanding of the practical side of data analysis for reliability related problems." (Roelof Coetzer, Data Science Group, Sasol South Africa)

"This is a well-written book which provides good insight into the statistical challenges and opportunities for successfully achieving product reliability for individuals who have completed at least the introductory course(s) in statistics. The target audience will include STEM students and academicians, business managers and professionals, engineers and others. Given the authors goal of attracting a broad audience, they present a wide array of real-world applications related to locomotives, aircraft engines, automobiles, medicine, and household appliance, etc." (Carolyn Morgan, MECK, Limited LLC) "I thoroughly enjoyed reading Achieving Product Reliability, and recommend it to engineers, technical and management level, and statisticians, both lecturers and research fellows, who are interested in reliability theory and data analysis." (Roelof L.J. Coetzer, Technometrics, 63:4, 5629564)

"The person reading this book will need to have an elementary understanding of statistics.These chapters focuses on the future of reliability and how this will impact us all in the various industries. Machine learning will also play a big part in the future of industries; this also is mentioned. For anyone studying a reliability field, this book is a must. A+"(Jacque van der Westhuizen, RAM Specialist-Sasol)

"Engineers and managers working in industries that utilize reliability methods on a regular basis should find this book useful. These chapters explain the "what and why" for applying reliability methods to real problems. The text is extremely clear, especially for such a technical topic. It is written for non-specialists, and is well-written for this audienceI would recommend publication, because I found this to be unique material, which would be of significant practical usefulness. Further, each of the authors is well-known in the field, adding further credibility to the work." (Roger Hoerl, Union College)

"The book will be of interest to academics and practitioners alike. For academics the book provides a broader range of applications of statistics in practice and industry. The way the authors discussed the examples are pitched at the right level for post-graduate engineering students to understand the importance of statistical thinking in reliability studies, and also for statistics students to provide an understanding of the practical side of data analysis for reliability related problems." (Roelof Coetzer, Data Science Group, Sasol South Africa)

"This is a well-written book which provides good insight into the statistical challenges and opportunities for successfully achieving product reliability for individuals who have completed at least the introductory course(s) in statistics. The target audience will include STEM students and academicians, business managers and professionals, engineers and others. Given the authors goal of attracting a broad audience, they present a wide array of real-world applications related to locomotives, aircraft engines, automobiles, medicine, and household appliance, etc." (Carolyn Morgan, MECK, Limited LLC)

Preface xv
Acknowledgments xxi
Authors xxiii
Chapter 1 Reliability And The Role Of Statistics: An Introduction 1(26)
1.1 Reliability: As The Customers See It
1(6)
1.2 What Is Reliability?
7(4)
1.3 Shift From A Reactive To A Proactive Mindset In Reliability Assurance
11(3)
1.4 Reliability Assurance Over The Entire Product Lifecycle
14(9)
Setting Reliability Goals
14(2)
Nonrepairable Products
15(1)
Repairable Products
16(1)
Evolution Of The Role Of Statistics In Reliability Assurance
16(14)
Reliability Evaluation Of A Conceptual Design (Chapter 2)
19(1)
Product Development And Assessment (Chapter 3)
19(2)
Reliability Validation (Chapter 4)
21(1)
Manufacturing (Chapter 5)
22(1)
Field Tracking (Chapters 6 And 7)
23(1)
Major Takeaways
23(1)
References And Additional Resources
24(3)
Chapter 2 System Reliability Evaluation Of A Conceptual Design 27(24)
2.1 System Reliability Modeling
29(1)
2.2 Reliability Block Diagrams
30(2)
Components In Series
30(1)
Components In Parallel
31(1)
Components In Series And Parallel
31(1)
2.3 Calculating System Reliability From Component Reliability
32(3)
Series Systems
33(1)
Parallel Systems
33(1)
More Complicated Systems
34(1)
2.4 Computer Tools For System Reliability Analysis
35(3)
2.5 System Reliability Example: Washing Machine Design
38(2)
System Description
38(1)
Reliability Model
38(1)
Subsystem Reliability Targets
39(1)
Introducing Redundancy
39(1)
2.6 Assumptions And Extensions
40(5)
Types Of Redundancy
40(1)
The Assumption Of Independence
41(1)
A Failure Of Perceived Redundancy
42(1)
Assessment Of Component Reliability
43(2)
2.7 Further Considerations
45(3)
Effect Of Part-Count Reduction
45(1)
Assessing The Reliability Of Different Size Products
45(3)
Assessing The Impact Of Removal Of A Failure Mode
48(1)
Major Takeaways
48(1)
References And Additional Resources
49(2)
Chapter 3 Product Reliability Development 51(36)
3.1 Paths To Reliability Improvement
51(5)
3.2 Design Of Experiments And Robust Design For Reliability
56(4)
3.3 Reliability Evaluation
60(23)
Use-Rate Acceleration
60(8)
Washing Machine Motor Example
60(1)
Testing Strategy
61(1)
The Test Plan
62(1)
Results After Six Months
63(2)
Results Assuming Elimination Of Plastic Part Failure Mode
65(2)
Further Evaluation And Testing
67(1)
Accelerated Life Tests
68(9)
Types Of Alts
68(1)
Acceleration Models
69(1)
Conducting An Alt
70(1)
Generator Insulation Example
70(1)
Test Plan And Protocol
71(1)
Results
72(1)
Analysis
73(2)
Further Considerations On Alts
75(2)
Degradation Testing
77(12)
Battery Example
78(1)
Degradation Measures
79(1)
Degradation Data
80(1)
Analysis Of Degradation Data
80(3)
Dangers Of Extrapolation
83(1)
Major Takeaways
83(1)
References And Additional Resources
84(3)
Chapter 4 Reliability Validation 87(24)
4.1 The Need For Reliability Validation
87(2)
4.2 In-House Testing
89(8)
Generator Insulation Example: Description
89(6)
An Unpleasant Discovery: A New Failure Mode
90(1)
Initial Analysis
91(2)
Separate Analyses By Failure Mode
93(2)
A Key Point: Obtain And Report All Relevant Data
95(2)
Validating Fixes
97(1)
4.3 Beta Site Testing
97(3)
Beta Site Testing Example: Laptop Computer Reliability Tracking System
99(1)
Limitations
99(1)
4.4 Reliability Growth Analysis
100(2)
Example
100(1)
Duane Plots
101(1)
4.5 Reliability Demonstration Test Planning
102(5)
Product Reliability Demonstration Test: The Concept
102(3)
Zero-Failure Reliability Demonstration Tests
103(1)
Distribution-Free Zero-Failure Reliability Demonstration Test Plan
103(1)
Further Comments On Distribution-Free Zero-Failure Reliability Demonstration Test Plans
104(1)
Zero-Failure Reliability Demonstration Test Plan Assuming A Weibull Distribution
104(1)
Application Of Preceding Plan To Bearing Life Example
105(1)
A Major Downside Of Zero-Failure Reliability Demonstration Tests
105(1)
Other Reliability Demonstration Test Plans
106(1)
What It All Adds Up To
106(1)
4.6 Product Safety
107(1)
4.7 Setting The Stage For Process-Focused Reliability Assurance In Manufacturing
108(2)
Major Takeaways
110(1)
References And Additional Resources
110(1)
Chapter 5 Reliability Assurance In Manufacturing 111(32)
5.1 Quality And Reliability Assurance In Manufacturing
112(1)
5.2 Evolution Of Reliability Assurance In Manufacturing
112(3)
5.3 Setting The Stage For Process-Focused Reliability Assurance In Manufacturing
115(10)
Identification Of Key Process Variables That Impact Reliability
116(1)
Measurement Capability
116(2)
Process Window
118(1)
Process Stability And Capability
119(1)
Process Surveillance Planning
120(1)
Statistical Process Monitoring
121(4)
5.4 Disciplined Approaches To Manufacturing Process Improvement
125(1)
5.5 Process Improvement Case Study: Stator Bar Manufacturing
126(12)
Define And Scope The Problem
128(1)
Capability And Stability Assessment
129(1)
Assessing Measurement Error
130(2)
Reducing Deviations From Target And Variability
132(5)
Fix Deviation From Target
132(1)
Find Root Causes Of Variability
133(2)
Understanding Major Source Of Variation
135(2)
Reducing Variability
137(1)
Validate
137(1)
Statistical Monitoring
137(1)
5.6 Product Reliability Testing
138(2)
Reliability Audit Testing
138(2)
Reliability Acceptance Testing
140(1)
5.7 Product Burn-In
140(1)
Major Takeaways
141(1)
References And Additional Resources
142(1)
Chapter 6 Field Reliability Tracking 143(30)
6.1 The Challenge Of Field Reliability Tracking
143(1)
6.2 Goals Of Reliability Tracking
144(2)
6.3 Reliability Tracking For Nonrepairable Products
146(13)
Laptop Computer Hard Drive Example
147(9)
Segmentation Analysis For A Laptop Computer Hard Drive
150(5)
Reporting And Corrective Action System
155(1)
Another Segmentation Example: Aircraft Engine Bleed System
156(3)
6.4 Reliability Tracking For Repairable Products
159(4)
Locomotive Braking Grid Example
159(4)
Segmentation Analysis For Locomotive Braking Grids Example
162(1)
6.5 Prediction Of Future Number Of Failures
163(7)
Washing Machine Circuit Board Example
164(15)
Field Failure Data Analysis On Circuit Boards
165(2)
Management Decision
167(1)
Prediction Of Future Number Of Failures
167(3)
6.6 Emerging Applications
170(1)
Major Takeaways
170(1)
References And Additional Resources
170(3)
Chapter 7 A Peek Into The Future 173(18)
7.1 The New Generation Of Reliability Data
173(6)
7.2 Applications In Reliability
179(7)
Product Maintenance Schedules
180(1)
Proactive Parts Replacement Strategies
181(1)
Automated Monitoring For Impending Failures
182(13)
Locomotive Engine Example
182(4)
7.3 Further Topics
186(2)
Major Takeaways
188(1)
References And Additional Resources
189(2)
Chapter 8 Statistical Concepts And Tools For Product Lifetime Data Analysis 191(26)
8.1 What's Different About Product Lifetime Data Analysis?
192(3)
8.2 Product Lifetime Distributions: Key Concepts
195(4)
Hazard Function
195(1)
The Weibull Distribution
196(2)
The Exponential Distribution
198(1)
The Lognormal Distribution
199(1)
8.3 Lifetime Data Analysis Case Study: Washing Machine Circuit Board Failures Data
199(11)
Information Sought
202(1)
General Approach To Lifetime Data Analysis
202(1)
Graphical Analysis
203(2)
Weibull Vs. Lognormal Distribution Analysis
205(1)
Estimation Of Model Parameters And Other Quantities Of Interest
206(4)
8.4 Further Topics
210(4)
Beware Of Extrapolation!
210(1)
Bayesian Methods In Lifetime Data Analysis
211(2)
Software For Statistical Analysis Of Reliability Data
213(1)
Major Takeaways
214(1)
References And Additional Resources
215(2)
Index 217
Dr. Necip Doganaksoy is an associate professor at the School of Business of Siena College, following a 26-year career in industry, mostly at General Electric (GE).

Dr. William Q. Meeker is a professor of statistics and distinguished professor of liberal arts and sciences at Iowa State University and a frequent consultant to industry.

Dr. Gerald J. Hahn is a retired manager of statistics at GE Global Research after a 46-year career at GE.

All three authors are Fellows of the American Society for Quality and the American Statistical Association, elected members of the International Statistical Institute, authors of three or more books, and recipients of numerous prestigious professional awards.