Reliability Engineering using Python

Software tools are a cornerstone of modern Reliability Engineering, enabling reliability practitioners to perform their analysis without getting bogged down in the details of the underlying mathematical processes. There are many software tools available for reliability engineering, some of which are tailored to this application, while others are more general statistical tools which can be adapted to the needs of reliability engineers. One thing these tools have in common is their graphical user interface (GUI). The GUI requires only a basic level of knowledge to operate, but with a few clicks of the correct buttons, the desired task can be achieved with relatively little mental effort. It is the user friendly GUI that draws reliability engineers to select such applications as their tools of choice for performing reliability engineering analyses.

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by nomtbf Leave a Comment

How About Weibull Instead of MTBF?

What About Weibull, Can I Use it Instead of MTBF?

This was a follow up question in a recent discussion with Alaa concerning using a metric other than MTBF.

The term ‘Weibull’ in some ways has become a synonym for reliability. Weibull analysis = life data (or reliability) analysis. The Weibull distribution has the capability to describe a changing failure rate, which is lacking when using just MTBF. Yet, it is suitable to use ‘Weibull’ as a metric? [Read more…]

by Dennis Craggs Leave a Comment

A Primer on Probability Distributions

The most common types of engineering data are measurements. There can be a few, thousands, or millions of data points to analyze. Without analytic tools, one can get lost in the data.

This article presents

Dotplots
Data if frequently clustered about a central value and displays variation.
Frequency histograms
Distribution characteristics
Normal Distributions

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High MTBF with Low Reliability

Can You Have a High MTBF and Low Reliability?

As regular readers know, MTBF by itself is misleading. When representing actual data it can be deceptive as well. Just because you have a high MTBF value doesn’t mean it is reliable.

In a previous article, 10 Reasons to Avoid MTBF, I mentioned that it is possible to have a relatively high MTBF value when the actual reliability is low. Ashley sent me the following note:

Hi Fred, i love reading your articles they are very informative. I have a question about something you said in a comment which i am hoping you will be able to clarify for me. You said products with higher MTBF can actually be less reliable than products with a lower MTBF

I have tried to find information on how this is possible online, and tried to do the maths myself to make this happen but i have to admit i am struggling.

No worries, Ashley, let’s work out an example to illustrate what I meant. [Read more…]

by Richard Coronado 2 Comments

Series System

During design and development, Reliability Engineers often receive reliability parameters in many forms. The most common reliability parameter is the mean time to failure (MTTF), which can also be specified as the failure rate (this is expressed as a frequency or Conditional Probability Density Function (PDF)) or the number of failures during a given period. [Read more…]