Practical Applications Of Reliability Engineering

Learn how to apply the fundamental reliability engineering concepts to your product.

What you'll learn
Understand reliability as a product requirement
Understand how reliability of the product changes over time
Calculate reliability of the product
Create probability density function of the product failure
Describe four characteristics of the failure distribution function and their practical application
Select the suitable probability distribution and find the key distribution characteristics for the given dataset
Understand two discrete and four continuous distributions that are essential for reliability analysis

Requirements
Basic Excel skills
Knowledge of school level math

Description
This course serves as an introduction to the field of reliability engineering and lays the foundation for learners to delve into more advanced concepts if they desire to do so. While technical specialists with substantial knowledge of reliability principles might find the content elementary.Reliability is frequently associated with the complexity of the mathematical formulas and theories required to be understood to start using the reliability concepts at work. However, the complexity of the mathematics behind reliability engineering should not deter technical specialists from using these concepts through existing technology, even without a complete understanding of the mathematical foundations.I have experience working and leading reliability engineering in the operation and maintenance (O&M) stages of complex assets. In practice, I frequently encounter barriers to implementing reliability analysis for two common reasons. The first reason is that it is not clear how and which reliability principles apply to O&M stages and how to implement them effectively. The second reason is not enough mathematical background to understand the principles and, therefore, difficulties in their implementation. As such, the benefits of reliability as a source of improving the effectiveness of preventative maintenance are frequently desirable but considered too difficult to implement. This course was created with the purpose of reducing or eliminating these two barriers.This course is designed to introduce fundamental reliability concepts and theories without delving into complex mathematics. The course materials include several Excel spreadsheets with pre-built formulas for reliability analysis that can be applied to the customer's data.Most of the course assignments are designed to develop the skills necessary for addressing reliability questions using the provided spreadsheets. Upon completion of the course, learners will be equipped to immediately apply these skills and materials to their own datasets.The course contains 6 sections. The first section explains what reliability and performance are from the perspective of the product or asset. Section two introduces reliability analysis and three main tools of the analysis. Section three explains how to measure reliability and introduces failure datasets used for analyses in the next sections. Section four introduces four moments of the failure distribution and describes how they can be used to draw conclusions from failure data. Section five explains the discrete (Binomial and Poisson) and continuous (Weibull, Exponential, Normal and Lognormal) distributions that are frequently used for reliability analysis. Section six concludes the training by describing the reliability considerations for the products over their lifecycle.

Engineers and technical specialists seeking to understand the fundamentals of reliability analysis and acquire skills in using standard reliability analysis tools.