Price loading...

Reliability Analysis Using MINITAB and Python

Electronics Engineering

Price data last checked 92 day(s) ago - refreshing...

View at Amazon

Price History & Forecast

No Price Data Available

Price history will appear here once data is collected from Amazon.

Price Distribution

No price data available for histogram

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.

Product Specifications

Format: hardcover
ASIN: 1119870763
Category: Books > Subjects > Science, Nature & Maths > Engineering & Technology > Electronics & Communications Engineering > Electronics Engineering
Domain: Amazon UK
Release Date: 27 October 2022
Listed Since: 14 September 2021

Barcode

No barcode data available

Reliability Analysis Using MINITAB and Python

Price History & Forecast

No Price Data Available

Price Distribution

Description

Product Specifications

Barcode

Similar Products You Might Like

Introduction to Reliability Engineering

Reliability Analysis with Minitab

Reliability Modelling: A Statistical Approach

Reliability Modelling: A Statistical Approach

System Reliability Theory: Models, Statistical Methods, and Applications (Wiley Series in Probability and Statistics)

Statistical Quality Control: Using MINITAB, R, JMP and Python

Reliability Assessments: Concepts, Models, and Case Studies

Probabilistic Reliability Models

Statistical Methods for the Reliability of Repairable Systems: 354 (Wiley Series in Probability and Statistics)

Reliability and Risk Analysis (What Every Engineer Should Know)

Probabilistic Reliability Engineering

Reliability and Risk Analysis (What Every Engineer Should Know)

Reliability Engineering: A Life Cycle Approach

Reliability and Risk: A Bayesian Perspective (Wiley Series in Probability and Statistics)

Elsevier Risk-Based Reliability Analysis and Risk Reduction

Engineering Systems Reliability, Safety, and Maintenance: An Integrated Approach

Reliability: Modeling, Prediction, and Optimization: 335 (Wiley Series in Probability and Statistics)

Reliability Engineering Advances

Engineering Systems Reliability, Safety, and Maintenance: An Integrated Approach

Weibull Models: 358 (Wiley Series in Probability and Statistics)

Probabilistic Reliability Analysis of Power Systems: A Student’s Introduction

Practical Reliability Engineering and Analysis for System Design and Life-Cycle Sustainment

Reliability Assessment of Safety and Production Systems: Analysis, Modelling, Calculations and Case Studies (Springer Series in Reliability Engineering)

Practical Applications of Bayesian Reliability (Quality and Reliability Engineering Series)