اسم المؤلف
Jaejin Hwang
التاريخ
11 فبراير 2024
المشاهدات
82
التقييم
(لا توجد تقييمات)
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Reliability Analysis Using MINITAB and Python
Jaejin Hwang
Northern Illinois University, USA
Contents
Cover
Title page
Copyright
About the Author
Preface
Acknowledgments
About the Companion Website
1 Introduction
1.1 Reliability Concepts
1.1.1 Reliability in Our Lives
1.1.2 History of Reliability
1.1.3 Definition of Reliability
1.1.4 Quality and Reliability
1.1.5 The Importance of Reliability
1.2 Failure Concepts
1.2.1 Definition of Failure
1.2.2 Causes of Failure
1.2.3 Types of Failure Time
1.2.4 The Reliability Bathtub Curve
1.3 Summary
2 Basic Concepts of Probability
2.1 Probability
2.1.1 The Importance of Probability in Reliability
2.2 Joint Probability with Independence
2.3 Union Probability
2.4 Conditional Probability2.5 Joint Probability with Dependence
2.6 Mutually Exclusive Events
2.7 Complement Rule
2.8 Total Probability
2.9 Bayes’ Rule
2.10 Summary
3 Lifetime Distributions
3.1 Probability Distributions
3.1.1 Random Variables
3.2 Discrete Probability Distribution
3.3 Continuous Probability Distribution
3.3.1 Reliability Concepts
3.3.2 Failure Rate
3.4 Exponential Distribution
3.4.1 Exponential Lack of Memory Property
3.4.2 Excel Practice
3.4.3 Minitab Practice
3.4.4 Python Practice
3.5 Weibull Distribution
3.5.1 Excel Practice
3.5.2 Minitab Practice
3.5.3 Python Practice
3.6 Normal Distribution
3.6.1 Excel Practice
3.6.2 Minitab Practice
3.6.3 Python Practice
3.7 Lognormal Distribution
3.7.1 Excel Practice3.7.2 Minitab Practice
3.7.3 Python Practice
3.8 Summary
4 Reliability Data Plotting
4.1 Straight Line Properties
4.2 Least Squares Fit
4.2.1 Excel Practice
4.2.2 Minitab Practice
4.2.3 Python Practice
4.3 Linear Rectification
4.4 Exponential Distribution Plotting
4.4.1 Excel Practice
4.4.2 Minitab Practice
4.4.3 Python Practice
4.5 Weibull Distribution Plotting
4.5.1 Minitab Practice
4.5.2 Python Practice
4.6 Normal Distribution Plotting
4.6.1 Minitab Practice
4.6.2 Python Practice
4.7 Lognormal Distribution Plotting
4.7.1 Minitab Practice
4.7.2 Python Practice
4.8 Summary
5 Accelerated Life Testing
5.1 Accelerated Testing Theory
5.2 Exponential Distribution Acceleration
5.3 Weibull Distribution Acceleration5.3.1 Minitab Practice
5.3.2 Python Practice
5.4 Arrhenius Model
5.4.1 Minitab Practice
5.4.2 Python Practice
5.5 Summary
6 System Failure Modeling
6.1 Reliability Block Diagram
6.2 Series System Model
6.3 Parallel System Model
6.4 Combined Serial–Parallel System Model
6.5 k-out-of-n System Model
6.6 Minimal Paths and Minimal Cuts
6.7 Summary
7 Repairable Systems
7.1 Corrective Maintenance
7.2 Preventive Maintenance
7.3 Mean Time between Failures
7.4 Mean Time to Repair
7.5 Availability
7.5.1 Inherent Availability
7.5.2 Achieved Availability
7.5.3 Operational Availability
7.5.4 System Availability
7.6 Maintainability
7.7 Preventive Maintenance Scheduling
7.7.1 Python Practice
7.8 Summary8 Case Studies
8.1 Parametric Reliability Analysis
8.1.1 Description of Case Study
8.1.2 Minitab Practice
8.1.3 Python Practice
8.2 Nonparametric Reliability Analysis
8.2.1 Description of Case Study
8.2.2 Minitab Practice
8.2.3 Python Practice
8.3 Driverless Car Failure Data Analysis
8.3.1 Description of Case Study
8.3.2 Minitab Practice
8.3.3 Python Practice
8.4 Warranty Analysis
8.4.1 Description of Case Study
8.4.2 Minitab Practice
8.5 Stress–Strength Interference Analysis
8.5.1 Description of Case Study
8.5.2 Minitab Practice
8.5.3 Python Practice
8.6 Summary
Index
End User License Agreement
List of Tables
Chapter 01
Table 1.1 Description of quality and reliability.
Table 1.2 Description of hard and soft failures.Table 1.3 Time to failure data of 10 components.
Chapter 03
Table 3.1 A probability mass function .
Table 3.2 The probability distribution for X.
Table 3.3 The failure characteristics with .
Chapter 04
Table 4.1 The coordinate data of x and y.
Table 4.2 Cumulative distribution function estimates .
Table 4.3 Median rank estimates of failure times.
Table 4.4 Median rank estimates of .
Table 4.5 The time to failure of 6 items.
Table 4.6 Readout failure data.
Table 4.7 Readout failure data and binomial estimates.
Table 4.8 Readout failure data and transformed CDF.
Table 4.9 Time to failure data of 17 components.
Table 4.10 Time to failure data of 10 components.
Table 4.11 Time to failure data of 15 components.
Chapter 05
Table 5.1 Various failure mechanisms and .
Table 5.2 Time to failure data .
Table 5.3 Readout data of failures .
Chapter 06
Table 6.1 The series system model .
Table 6.2 The parallel system model .
Chapter 08Table 8.1 Time to failure data of loader tires.
Table 8.2 Failure data of furnace components.
Table 8.3 Disengagement data of Google vehicle.
Table 8.4 Disengagement data of Nissan vehicle.
Table 8.5 Disengagement data of Mercedes-Benz vehicle.
Table 8.6 Disengagement data of Volkswagen vehicle.
Table 8.7 Disengagement data of Bosch vehicle.
Table 8.8 Disengagement data of Delphi vehicle.
Table 8.9 Example of the warranty data format.
Table 8.10 Historical warranty data of vacuum products.
List of Illustrations
Chapter 01
Figure 1.1 The factor of 10 rule.
Figure 1.2 The adverse effects of failure.
Figure 1.3 Frequency distribution of .
Figure 1.4 Frequency distribution of .
Figure 1.5 Frequency distribution of .
Figure 1.6 Description of the .
Figure 1.7 Description of right .
Figure 1.8 Description of left-censored failure time.
Figure 1.9 Description of interval-censored failure time.
Figure 1.10 Data set with Minitab.
Figure 1.11 Python codes to .
Figure 1.12 Right-censored data .Figure 1.13 The reliability bathtub .
Figure 1.14 Python codes used .
Figure 1.15 The reliability bathtub .
Chapter 02
Figure 2.1 Joint probability.
Figure 2.2 Union probability.
Figure 2.3 Mutually exclusive events.
Figure 2.4 Complement rule.
Figure 2.5 Total probability.
Chapter 03
Figure 3.1 Probability distribution of .
Figure 3.2 The probability density .
Figure 3.3 The probability density .
Figure 3.4 The cumulative distribution .
Figure 3.5 Exponential reliability function .
Figure 3.6 Probability Distribution Plot .
Figure 3.7 Vary Parameters function .
Figure 3.8 PDF of the .
Figure 3.9 PDF of the .
Figure 3.10 Python codes used .
Figure 3.11 The exponential distribution .
Figure 3.12 Python codes to .
Figure 3.13 Exponential CDF with .
Figure 3.14 Weibull probability density .
Figure 3.15 Weibull cumulative distribution .Figure 3.16 Weibull cumulative distribution .
Figure 3.17 Weibull reliability function .
Figure 3.18 Weibull PDF with .
Figure 3.19 Weibull PDF with .
Figure 3.20 Python codes used .
Figure 3.21 The Weibull distribution .
Figure 3.22 The normal distribution.
Figure 3.23 The 68-95-99.7 rule of the normal distribution.
Figure 3.24 Normal cumulative distribution function.
Figure 3.25 Normal reliability function.
Figure 3.26 Normal failure rate function.
Figure 3.27 Standard normal distribution.
Figure 3.28 Normal distribution PDF setup.
Figure 3.29 Normal distribution PDF .
Figure 3.30 Python codes used .
Figure 3.31 The normal distribution .
Figure 3.32 Lognormal probability density .
Figure 3.33 Lognormal probability density .
Figure 3.34 Lognormal cumulative distribution .
Figure 3.35 Lognormal PDF setup .
Figure 3.36 Lognormal PDF with .
Figure 3.37 Python codes used .
Figure 3.38 The lognormal distribution .
Figure 3.39 Python codes for .
Figure 3.40 The distribution explorer .Figure 3.41 The Python codes .
Figure 3.42 The top three .
Chapter 04
Figure 4.1 Properties of the .
Figure 4.2 Example of the .
Figure 4.3 Deviation of the .
Figure 4.4 A scatter plot .
Figure 4.5 A scatter plot .
Figure 4.6 Python codes for .
Figure 4.7 The least squares .
Figure 4.8 The CDF estimates .
Figure 4.9 A regression line .
Figure 4.10 Probability plot using .
Figure 4.11 Minitab worksheet .
Figure 4.12 Probability plot of the exponential .
Figure 4.13 Minitab data worksheet .
Figure 4.14 Probability plot of .
Figure 4.15 Python codes used .
Figure 4.16 The exponential probability .
Figure 4.17 The exponential probability .
Figure 4.18 The Weibull probability .
Figure 4.19 The data set .
Figure 4.20 The Weibull probability .
Figure 4.21 The Python codes .
Figure 4.22 The Weibull probability .Figure 4.23 The Excel data .
Figure 4.24 The Python codes .
Figure 4.25 The Weibull probability .
Figure 4.26 The normal probability .
Figure 4.27 The normal probability .
Figure 4.28 The Python codes .
Figure 4.29 The normal probability .
Figure 4.30 The lognormal probability .
Figure 4.31 The data set .
Figure 4.32 The lognormal probability .
Figure 4.33 The Python codes .
Figure 4.34 The lognormal probability .
Chapter 05
Figure 5.1 Accelerated testing theory .
Figure 5.2 Minitab failure time .
Figure 5.3 Probability plots of .
Figure 5.4 Probability plots with .
Figure 5.5 Python codes were .
Figure 5.6 The Weibull distribution .
Figure 5.7 Minitab readout data .
Figure 5.8 Probability plots of .
Figure 5.9 Probability plots with .
Figure 5.10 Python codes to .
Figure 5.11 The AF in .
Chapter 06Figure 6.1 The reliability block .
Figure 6.2 Series system model .
Figure 6.3 Parallel system model .
Figure 6.4 Combined serial– .
Figure 6.5 Combined serial– .
Figure 6.6 High-level and .
Figure 6.7 2-out-of .
Figure 6.8 A bridge structure.
Figure 6.9 RBD of a bridge structure.
Figure 6.10 Combined serial– .
Figure 6.11 Combined serial– .
Figure 6.12 RBD of the .
Figure 6.13 Combined serial– .
Figure 6.14 The fault tree diagram.
Figure 6.15 Converting the fault tree diagram to an RBD.
Figure 6.16 The bridge structure with five components.
Figure 6.17 The RBD of minimal cuts.
Figure 6.18 Combined serial– .
Chapter 07
Figure 7.1 Illustration of the .
Figure 7.2 The illustration of .
Figure 7.3 Reliability bathtub curve .
Figure 7.4 The cost related .
Figure 7.5 Python codes to .
Figure 7.6 The optical replacement .Chapter 08
Figure 8.1 Data entry in .
Figure 8.2 Selection of distribution ID plot.
Figure 8.3 Distribution ID Plot-Right Censoring.
Figure 8.4 Distribution ID plot for time to failure (hour).
Figure 8.5 Selection of Distribution Overview Plot.
Figure 8.6 Distribution Overview Plot .
Figure 8.7 Distribution overview plot .
Figure 8.8 Selecting Parametric Distribution .
Figure 8.9 Parametric Distribution Analysis .
Figure 8.10 Parametric Distribution Analysis .
Figure 8.11 Parametric Distribution Analysis .
Figure 8.12 Parametric Distribution Analysis .
Figure 8.13 Cumulative Failure Plot .
Figure 8.14 Complete Python code .
Figure 8.15 Distribution ID plot.
Figure 8.16 Results for the .
Figure 8.17 Python codes of .
Figure 8.18 The distribution overview .
Figure 8.19 Python codes for .
Figure 8.20 The output of .
Figure 8.21 The exact and .
Figure 8.22 Nonparametric distribution analysis .
Figure 8.23 Nonparametric distribution analysis .
Figure 8.24 Nonparametric distribution analysis .Figure 8.25 Nonparametric distribution analysis .
Figure 8.26 Survival plot with .
Figure 8.27 Minitab outputs of .
Figure 8.28 Python codes to .
Figure 8.29 Survival plot of .
Figure 8.30 Python output of .
Figure 8.31 Disengagement data set .
Figure 8.32 Distribution ID plot .
Figure 8.33 Distribution ID plot .
Figure 8.34 Distribution overview plot .
Figure 8.35 Distribution overview plot .
Figure 8.36 Merged data set .
Figure 8.37 Probability plots of .
Figure 8.38 Distribution overview plots .
Figure 8.39 Survival plot for .
Figure 8.40 Hazard plot for .
Figure 8.41 Python codes to .
Figure 8.42 Probability plots of .
Figure 8.43 Probability plots of .
Figure 8.44 Python codes to .
Figure 8.45 Distribution overview plots .
Figure 8.46 Warranty data set in Minitab.
Figure 8.47 Pre-process warranty data.
Figure 8.48 Pre-process warranty data setup.
Figure 8.49 Reformatted warranty data set.Figure 8.50 Distribution ID plot.
Figure 8.51 Distribution ID plot setup.
Figure 8.52 Probability plots.
Figure 8.53 Warranty prediction.
Figure 8.54 Warranty prediction setup.
Figure 8.55 Warranty prediction results.
Figure 8.56 Summary of current warranty claims.
Figure 8.57 Table of predicted number of failures.
Figure 8.58 Predicted number of failures plot.
Figure 8.59 Probability Distribution Plot .
Figure 8.60 Two Distributions option .
Figure 8.61 Two distributions setup .
Figure 8.62 Stress and strength .
Figure 8.63 Python codes used .
Figure 8.64 The stress
Index
aA
cceleration factor 116
Accelerated life testing 115
Achieved availability 154
Activation energy 123
Anderson–Darling values 169
Arrhenius model 123
Availability 153
b
Bayes’ rule 25
Benard’s approximation 87
Binomial estimate 90
Binomial formula 141
c
Censored failure time 9
Characteristic life 46
Combined serial-parallel system model 138
Complement rule 24
Conditional probability 22Continuous probability distribution 32
Corrective maintenance 151
Crosshairs function 45
d
Discrete probability distribution 30
e
Early life 13
Exact failure time 8
Exponential distribution 37
Exponential distribution acceleration 117
Exponential distribution plotting 84
fF
ails in Time 35
Failure 5
Failure order 87
Failure rate 35
Fault tree diagram 146
h
Hard failure 5
High level redundancy 140i
Inherent availability 153
Initial Quality Index 3
Intercept 78
Interval-censored failure time 9
j
J.D. Power and Associates 3
Joint probability with dependence 22
Joint probability with independence 20
k
k-out-of-n system model 140
l
Lack of memory property 40
Least squares fit 79
Left-censored failure time 9
Linear acceleration 116
Linear rectification 84
Lognormal distribution 63
Lognormal distribution plotting 106
Low level redundancy 140
mMaintainability 156
Maintenance hours per operating hour 156
Mean down time 155
Mean time between failures 152
Mean time between maintenance activities 155
Mean time to failure 50
Mean time to repair 153
Median rank estimate 85
Minimal cuts 142
Minimal paths 142
Mutually exclusive events 23
n
Nonparametric reliability analysis 184
Normal distribution 54
Normal distribution plotting 103
o
Operational availability 155
Overstress 5
pP
arallel system model 135
Parametric reliability analysis 165
Percent per thousand hours 35Preventive maintenance 152
Preventive maintenance scheduling 157
Probability 19
q
Quality 3
rR
andom variables 29
Readout data 90
Reliability 2
Reliability bathtub curve 12
Reliability block diagram 131
Repairable systems 151
Right-censored failure time 9
s
Series system model 132
Similar distribution finder 70
Slope parameter 78
Soft failure 5
Straight line properties 77
Stress-strength interference analysis 210
Survival plot 187
System availability 156System failure modeling 131
t
The distribution explorer 69
The factor of 10 rule 4
Time to failure 116
Total probability 24
u
Union probability 21
Useful life 13
vV
ariation 6
Vehicle Dependability Study Index 4
wW
arranty analysis 202
Wearout 7
Wearout life 14
Weibull distribution 46
Weibull distribution acceleration 118
Weibull distribution plotting 96

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