Reliability Analysis Using Minitab and Python (Hardcover)

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 exercise 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 syste 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.

《使用 Minitab 和 Python 进行可靠性分析》是一本全面介绍可靠性分析理论和基础知识的教材，同时结合 Minitab 和 Python 工具进行实际应用。本书详细讲解了如何使用这两种编程语言实现统计分布和可靠性分析方法，帮助读者有效地处理大量数据并减少人为错误。

本书通过示例、案例研究、练习和问题等方式，提供了一个流畅的学习体验。书中还提供了包含样本数据、Minitab 和 Python 示例文件的 Excel 文件。

本书适合具备基本概率和统计知识的学生阅读，但也在开头涵盖了基本统计学的内容，因此对于不熟悉统计学的学生也易于理解。

本书由该领域的高度资深作者撰写，涵盖的主题包括：

- 建立基本的统计背景，重点介绍概率、联合概率、并集概率、条件概率、互斥事件和贝叶斯定理。
- 统计分布，重点介绍离散情况、连续情况、指数分布、Weibull 分布、正态分布和对数正态分布。
- 可靠性数据绘图，重点介绍直线特性、最小二乘拟合、线性修正、精确故障时间和读取故障数据。
- 加速寿命测试，重点介绍加速测试理论、指数分布加速和Weibull 分布加速。
- 系统故障建模，重点介绍可靠性框图、串联系统模型、并联系统模型、k-out-of-n 系统模型以及最小路径和最小割。
- 可修复系统，重点介绍纠正性和预防性维护、可用性、可维护性和预防性维护计划。

《使用 Minitab 和 Python 进行可靠性分析》是一本适合本科和研究生学生阅读的优秀入门教材。它以清晰简明的方式呈现信息，并提供了许多有助于理解概念、保持信息和实际应用的辅助学习资源。

Dr. Jaejin Hwang is Associate Professor in the Industrial and Systems Engineering Department at Northern Illinois University, USA. He received his PhD in Industrial and Systems Engineering from Ohio State University, USA, in 2016 and has published two books with CRC Press and Mercury Learning & Information respectively. He has also been a guest editor for the International Journal of Environmental Research and Public Health.

Dr. Jaejin Hwang 是美國北伊利諾伊大學工業與系統工程系的副教授。他於2016年從美國俄亥俄州立大學獲得工業與系統工程博士學位，並分別與CRC Press和Mercury Learning & Information出版了兩本書籍。他還擔任過《國際環境研究與公共衛生期刊》的客座編輯。