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E-raamat: Reliability Data Analysis with Excel and Minitab

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(Southern Polytechnic State Univ. United Nations Industrial Development Organization United Nations Industrial Development Organization United Nations Industrial Development Organization Southern Polytechnic State Univ. Southern Polytechn)
  • Formaat: 361 pages
  • Ilmumisaeg: 30-Aug-2011
  • Kirjastus: ASQ Quality Press
  • Keel: eng
  • ISBN-13: 9781636940441
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Reliability Data Analysis with Excel and MinitabSuurem pilt
  • Formaat: 361 pages
  • Ilmumisaeg: 30-Aug-2011
  • Kirjastus: ASQ Quality Press
  • Keel: eng
  • ISBN-13: 9781636940441
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A quality engineer with half a century of experience, Stephens offers a user's manual or a supplement to a traditional textbook in a course on analyzing reliability data using the two popular software packages, Excel and Minitab. He takes care to describe only elementary features of the software, focusing on analysis techniques rather than computer adeptness. His topics include basic generic reliability relationships, the point and interval estimation for discrete distributions, linear rectification of reliability models for least squares estimation of parameters, Weibull and extreme-value distributions, logistic and log-logistic distributions, and determining reliability with accelerated life testing. Annotation ©2012 Book News, Inc., Portland, OR (booknews.com)
CD-ROM Contents xiii
List of Figures and Tables
xvii
Chapter 1 Introduction to Reliability and the Text
1(8)
1.0 Introduction
1(1)
2.0 Approach Taken by Text
2(3)
3.0 Topic and
Chapter Summary
5(4)
Chapter 2 Basic Generic Reliability Relationships
9(24)
1.0 The Cumulative Distribution Function (CDF), F(x)
9(3)
2.0 The Reliability Function, R(t)
12(3)
3.0 The Failure Rate or Hazard Function, h(t)
15(2)
4.0 The Cumulative Hazard Function, H(t)
17(1)
5.0 The Average Failure Rate, AFR(t1, t2) or AFR(τ)
18(1)
6.0 The Mean Time to Failure, MTTF
19(1)
7.0 Hazard Function, h(t), Modeling
20(1)
8.0 DFR, IFR, and Constant Failure Rates and the "Bathtub Curve"
21(1)
9.0 Failure Rate or Rate of Occurrence of Failures (ROCOF)
22(2)
10.0 Aspects of Reliability Data
24(6)
10.1 Complete and Censored Data
24(3)
10.2 Interval-Censored Data
27(1)
10.3 Multi-Censored Data
28(1)
10.4 Left-Censored Data
29(1)
10.5 Reliability Testing
29(1)
11.0 Probability Distribution Functions
30(1)
12.0 Generic Reliability Relationships
31(2)
Chapter 3 Some Useful Discrete Distributions for Reliability Analysis
33(46)
1.0 Introduction
33(1)
2.0 Discrete Probability Distribution Functions
34(45)
2.1 Hypergeometric Distribution Function
34(11)
2.2 Binomial Distribution Function
45(6)
2.3 The f Binomial Function---Hypergeometric Approximation
51(1)
2.4 The Negative Binomial Distribution Function
52(12)
2.5 The Geometric Distribution Function
64(5)
2.6 The Poisson Distribution Function
69(10)
Chapter 4 Point and Interval Estimation for Discrete Distributions
79(30)
1.0 Introduction
79(2)
2.0 Hypergeometric and Negative Hypergeometric Distributions
81(9)
2.1 Example 4-1 Hypergeometric Confidence Intervals
83(3)
2.2 Example 4-2 Hypergeometric Confidence Interval Computations
86(3)
2.3 Negative Hypergeometric
89(1)
3.0 Binomial Distribution
90(8)
3.1 Example 4-4 Confidence Limits and Intervals for Binomial Proportion
93(3)
3.2 Example 4-5 Confidence Intervals for Binomial Proportion via Minitab
96(2)
4.0 Negative Binomial Distribution
98(5)
4.1 Example 4-6 Confidence Limits and Intervals for Negative Binomial
100(2)
4.2 Example 4-7 Confidence Intervals for Negative Binomial Proportion via Minitab
102(1)
5.0 Poisson Distribution
103(6)
5.1 Example 4-8 Poisson Confidence Limits
106(1)
5.2 Example 4-9 Confidence Intervals for Poisson via Minitab
107(2)
Chapter 5 Linear Rectification of Reliability Models For Least Squares Estimation of Parameters
109(36)
1.0 Introduction
109(1)
2.0 Least Squares Procedure
109(11)
2.1 Estimating F(t)
112(8)
3.0 Exponential Distribution
120(8)
3.1 Example 5-2---CDF Method---Complete Data
121(1)
3.2 Example 5-2---CDF Method---Censored Data
122(1)
3.3 Example 5-2---Cum Hazard Rate Method---Complete Data
123(2)
3.4 Example 5-2---Cum Hazard Rate Method---Censored Data
125(1)
3.5 Example 5-2---Readout or Interval Data Analysis via Least Squares---Complete
125(1)
3.6 Example 5-2---Readout or Interval Data Analysis via Least Squares---Censored
126(1)
3.7 Approximate Parameter Estimation from Graphs---Exponential
127(1)
4.0 Normal and Lognormal Distributions
128(5)
4.1 Normal Distribution
128(2)
4.2 Lognormal Distribution
130(3)
5.0 Weibull Distribution
133(4)
5.1 Example 5-5---CDF Method---Complete Data
134(1)
5.2 Example 5-5---CDF Method---Censored Data
135(1)
5.3 Example 5-7---CDF Method---Interval Data with Truncation
135(1)
5.4 Approximate Parameter Estimation from Graphs---Weibull
136(1)
6.0 Extreme-Value Distributions
137(2)
6.1 Example 5-6---CDF Method---Complete Data
138(1)
7.0 Logistic and Log-Logistic Distributions
139(2)
7.1 Example 5-7---CDF Method---Complete Data
140(1)
8.0 Minitab's Simulation Capabilities
141(4)
8.1 Change of Variable and the Probability Integral Transformation
142(3)
Chapter 6 Exponential, Gamma, and Chi-Square (Χ2) Distributions
145(46)
1.0 Introduction
145(1)
2.0 The Exponential Distribution
146(9)
2.1 The Exponential Average Failure Rate, AFR(t1, t2) or AFR(τ)
148(1)
2.2 Mean Time to Failure for the Exponential Model
148(2)
2.3 Percentile Function and Median, Mean, and Variance
150(1)
2.4 Lack of Memory for the Exponential Model
151(1)
2.5 Failure Rate Scaling Units
152(1)
2.6 The Exponential Distribution and System Reliability---Closure Property
153(2)
3.0 The Gamma Distribution
155(4)
3.1 The Gamma, Poisson, and Negative Binomial Relationships
157(2)
4.0 The Chi-square (Χ2) Distribution
159(14)
4.1 Goodness-of-Fit Tests
162(11)
5.0 Point and Interval Estimation for the Exponential Distribution
173(18)
5.1 Confidence Limits and Intervals for Parameters λ and θ
175(6)
5.2 Confidence Limits and Intervals for Reliability
181(1)
5.3 The Case of Zero Failures
182(4)
5.4 Test Characteristics Determination---Planning
186(3)
5.5 Exponential Distribution Analysis via Minitab
189(1)
5.6 Exponential Distribution Simulation
190(1)
Chapter 7 Weibull and Extreme-Value Distributions
191(24)
1.0 Introduction
191(1)
2.0 The Weibull Distribution
192(14)
2.1 The Weibull Average Failure Rate, AFR(t1, t2) or AFR(T)
197(1)
2.2 Mean Time to Failure (MTTF) for the Weibull Distribution
197(1)
2.3 Percentile Function, Median, and Variance
198(1)
2.4 The Weibull Distribution and System Reliability---Closure Property
199(2)
2.5 Point and Interval Estimation for the Weibull Distribution
201(2)
2.6 Weibull Distribution Reliability/Survival Examples
203(3)
3.0 The Smallest Extreme-Value Distribution
206(7)
3.1 The Principal Functions
207(2)
3.2 The SEV Average Failure Rate, AFR(t1, t2) or AFR(T)
209(1)
3.3 Mean, Median, Mode, Variance, and Percentile Function
210(1)
3.4 SEV Distribution Estimation and Examples
211(2)
4.0 Weibull and SEV Distribution Simulation
213(2)
Chapter 8 Normal and Lognormal Distributions
215(22)
1.0 Introduction
215(1)
2.0 The Normal Distribution
216(10)
2.1 Mean, Median, Mode, Variance, and Percentile Function
219(1)
2.2 The Central Limit Theorem and Its Practical Consequences
220(2)
2.3 Strength-Stress Analysis via Normal Distributions
222(2)
2.4 Point and Interval Estimation for the Normal Distribution
224(1)
2.5 Normal Distribution Reliability/Survival Example
225(1)
3.0 The Lognormal Distribution
226(8)
3.1 Mean, Median, Mode, Variance, and Percentile Function
230(1)
3.2 Point and Interval Estimation for the Lognormal Distribution
231(1)
3.3 Lognormal Distribution Reliability/Survival Example
232(2)
4.0 Normal and Lognormal Distribution Simulation
234(3)
Chapter 9 Logistic and Log-Logistic Distributions
237(16)
1.0 Introduction
237(1)
2.0 The Logistic Distribution
238(7)
2.1 Mean, Median, Mode, Variance, and Percentile Function
241(1)
2.2 Point and Interval Estimation for the Logistic Distribution
242(1)
2.3 Logistic Distribution Reliability/Survival Example
243(2)
3.0 The Log-Logistic Distribution
245(6)
3.1 Mean, Median, Mode, Variance, and Percentile Function
248(2)
3.2 Point and Interval Estimation for the Logistic Distribution
250(1)
4.0 Logistic and Log-Logistic Distribution Simulation
251(2)
Chapter 10 Systems Reliability
253(14)
1.0 Introduction
253(1)
2.0 Series Systems
254(2)
3.0 Parallel or Active Redundancy Systems
256(4)
3.1 Parallel or Active Redundancy Systems, k out of n
258(1)
3.2 Parallel or Active Redundancy Shared Load Systems
259(1)
4.0 Standby Redundancy Systems
260(4)
5.0 Larger Systems---Series and Parallel Subsystems Combined
264(1)
6.0 More-Complex Systems
265(2)
Chapter 11 Reliability of Repairable Systems
267(32)
1.0 Introduction
267(2)
2.0 Example 11-1 System Age--Inter-arrival Time--Data Analysis
269(4)
3.0 Homogeneous Poisson Process
273(7)
4.0 Non-Homogeneous Poisson Process, Power-Law Model, and Trend Tests
280(17)
4.1 Power-Law Model
281(5)
4.2 Trend Tests
286(11)
5.0 Summary
297(2)
Chapter 12 Reliability Determination via Accelerated Life Testing
299(22)
1.0 Introduction
299(2)
2.0 Acceleration Factors and Relationships
301(6)
2.1 Example 12-1 Multiple Accelerated Levels Analysis
304(3)
3.0 Arrhenius Model
307(4)
4.0 Inverse Power Law Model
311(4)
5.0 The General Eyring Model and Useful Two-Stress Forms
315(4)
6.0 Summary
319(2)
References 321(10)
Index 331
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