Reliability Analysis Using MINITAB and Python

Reliability Analysis Using MINITAB and Python

by Jaejin Hwang
Released November 2022
Publisher(s): Wiley
ISBN: 9781119870760

Read it now on the O’Reilly learning platform with a 10-day free trial.

O’Reilly members get unlimited access to books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.

Start your free trial

Book description

Reliability Analysis Using MINITAB and Python

Complete overview of the theory and fundamentals of Reliability Analysis applied with Minitab and Python tools

Reliability Analysis Using Minitab and Python expertly applies Minitab and Python programs to the field of reliability engineering, presenting basic concepts and explaining step-by-step how to implement statistical distributions and reliability analysis methods using the two programming languages. The textbook enables readers to effectively use software to efficiently process massive amounts of data while also reducing human error.

Examples and case studies as well as exercises and questions are included throughout to enable a smooth learning experience. Excel files containing the sample data and Minitab and Python example files are also provided.

Students who have basic knowledge of probability and statistics will find this textbook highly approachable. Nonetheless, it also covers material on basic statistics at the beginning, so students who are not familiar with statistics can follow the material as well.

Written by a highly qualified author in the field, sample topics covered in Reliability Analysis Using Minitab and Python include:

  • Establishing a basic statistical background, with a focus on probability, joint probability, union probability, conditional probability, mutually exclusive events, and bayes’ rule
  • Statistical distributions, with a focus on discrete cases, continuous cases, exponential distribution, Weibull distribution, normal distribution, and lognormal distribution
  • Reliability data plotting, with a focus on straight line properties, least squares fit, linear rectification, exact failure times, and readout failure data
  • Accelerated life testing, with a focus on accelerated testing theory, exponential distribution acceleration, and Weibull distribution acceleration
  • System failure modeling, with a focus on reliability block diagram, series system model, parallel system model, k-out-of-n system model, and minimal paths and minimal cuts.
  • Repairable systems, with a focus on corrective and preventive maintenances, availability, maintainability, and preventive maintenance scheduling

Reliability Analysis Using Minitab and Python serves as an excellent introductory level textbook on the topic for both undergraduate and graduate students. It presents information clearly and concisely and includes many helpful additional learning resources to aid in understanding of concepts, information retention, and practical application.

Table of contents

  1. Cover
  2. Title page
  3. Copyright
  4. About the Author
  5. Preface
  6. Acknowledgments
  7. About the Companion Website
  8. 1 Introduction
    1. 1.1 Reliability Concepts
      1. 1.1.1 Reliability in Our Lives
      2. 1.1.2 History of Reliability
      3. 1.1.3 Definition of Reliability
      4. 1.1.4 Quality and Reliability
      5. 1.1.5 The Importance of Reliability
    2. 1.2 Failure Concepts
      1. 1.2.1 Definition of Failure
      2. 1.2.2 Causes of Failure
      3. 1.2.3 Types of Failure Time
      4. 1.2.4 The Reliability Bathtub Curve
    3. 1.3 Summary
  9. 2 Basic Concepts of Probability
    1. 2.1 Probability
      1. 2.1.1 The Importance of Probability in Reliability
    2. 2.2 Joint Probability with Independence
    3. 2.3 Union Probability
    4. 2.4 Conditional Probability
    5. 2.5 Joint Probability with Dependence
    6. 2.6 Mutually Exclusive Events
    7. 2.7 Complement Rule
    8. 2.8 Total Probability
    9. 2.9 Bayes’ Rule
    10. 2.10 Summary
  10. 3 Lifetime Distributions
    1. 3.1 Probability Distributions
      1. 3.1.1 Random Variables
    2. 3.2 Discrete Probability Distribution
    3. 3.3 Continuous Probability Distribution
      1. 3.3.1 Reliability Concepts
      2. 3.3.2 Failure Rate
    4. 3.4 Exponential Distribution
      1. 3.4.1 Exponential Lack of Memory Property
      2. 3.4.2 Excel Practice
      3. 3.4.3 Minitab Practice
      4. 3.4.4 Python Practice
    5. 3.5 Weibull Distribution
      1. 3.5.1 Excel Practice
      2. 3.5.2 Minitab Practice
      3. 3.5.3 Python Practice
    6. 3.6 Normal Distribution
      1. 3.6.1 Excel Practice
      2. 3.6.2 Minitab Practice
      3. 3.6.3 Python Practice
    7. 3.7 Lognormal Distribution
      1. 3.7.1 Excel Practice
      2. 3.7.2 Minitab Practice
      3. 3.7.3 Python Practice
    8. 3.8 Summary
  11. 4 Reliability Data Plotting
    1. 4.1 Straight Line Properties
    2. 4.2 Least Squares Fit
      1. 4.2.1 Excel Practice
      2. 4.2.2 Minitab Practice
      3. 4.2.3 Python Practice
    3. 4.3 Linear Rectification
    4. 4.4 Exponential Distribution Plotting
      1. 4.4.1 Excel Practice
      2. 4.4.2 Minitab Practice
      3. 4.4.3 Python Practice
    5. 4.5 Weibull Distribution Plotting
      1. 4.5.1 Minitab Practice
      2. 4.5.2 Python Practice
    6. 4.6 Normal Distribution Plotting
      1. 4.6.1 Minitab Practice
      2. 4.6.2 Python Practice
    7. 4.7 Lognormal Distribution Plotting
      1. 4.7.1 Minitab Practice
      2. 4.7.2 Python Practice
    8. 4.8 Summary
  12. 5 Accelerated Life Testing
    1. 5.1 Accelerated Testing Theory
    2. 5.2 Exponential Distribution Acceleration
    3. 5.3 Weibull Distribution Acceleration
      1. 5.3.1 Minitab Practice
      2. 5.3.2 Python Practice
    4. 5.4 Arrhenius Model
      1. 5.4.1 Minitab Practice
      2. 5.4.2 Python Practice
    5. 5.5 Summary
  13. 6 System Failure Modeling
    1. 6.1 Reliability Block Diagram
    2. 6.2 Series System Model
    3. 6.3 Parallel System Model
    4. 6.4 Combined Serial–Parallel System Model
    5. 6.5 k-out-of-n System Model
    6. 6.6 Minimal Paths and Minimal Cuts
    7. 6.7 Summary
  14. 7 Repairable Systems
    1. 7.1 Corrective Maintenance
    2. 7.2 Preventive Maintenance
    3. 7.3 Mean Time between Failures
    4. 7.4 Mean Time to Repair
    5. 7.5 Availability
      1. 7.5.1 Inherent Availability
      2. 7.5.2 Achieved Availability
      3. 7.5.3 Operational Availability
      4. 7.5.4 System Availability
    6. 7.6 Maintainability
    7. 7.7 Preventive Maintenance Scheduling
      1. 7.7.1 Python Practice
    8. 7.8 Summary
  15. 8 Case Studies
    1. 8.1 Parametric Reliability Analysis
      1. 8.1.1 Description of Case Study
      2. 8.1.2 Minitab Practice
      3. 8.1.3 Python Practice
    2. 8.2 Nonparametric Reliability Analysis
      1. 8.2.1 Description of Case Study
      2. 8.2.2 Minitab Practice
      3. 8.2.3 Python Practice
    3. 8.3 Driverless Car Failure Data Analysis
      1. 8.3.1 Description of Case Study
      2. 8.3.2 Minitab Practice
      3. 8.3.3 Python Practice
    4. 8.4 Warranty Analysis
      1. 8.4.1 Description of Case Study
      2. 8.4.2 Minitab Practice
    5. 8.5 Stress–Strength Interference Analysis
      1. 8.5.1 Description of Case Study
      2. 8.5.2 Minitab Practice
      3. 8.5.3 Python Practice
    6. 8.6 Summary
  16. Index
  17. End User License Agreement

Product information

  • Title: Reliability Analysis Using MINITAB and Python
  • Author(s): Jaejin Hwang
  • Release date: November 2022
  • Publisher(s): Wiley
  • ISBN: 9781119870760