The 2 Parameter Weibull Distribution 7 Formulas

This is part of a short series on the common life data distributions.

The Weibull distribution is both popular and useful. It has some nice features and flexibility that support its popularity. This short article focuses on 7 formulas of the Weibull Distribution.

If you want to know more about fitting a set of data to a distribution, well that is in another article.

It has the essential formulas that you may find useful when answering specific questions. Knowing a distribution’s set of parameters does provide, along with the right formulas, a quick means to answer a wide range of reliability related questions. [Read more…]

by Fred Schenkelberg Leave a Comment

How to Calculate Reliability Given 3 Different Distributions

On occasion, we want to estimate the reliability of an item at a specific time.

Maybe we are considering extending the warranty period, for example, and want to know the probability of no failures over one year instead of over the current 3 months.

Or, let’s say you talked to a bearing vendor and have the Weibull parameters and wish to know the reliability value over 2 years.

Whatever specific situation, you have the life distributions parameters. You just need to calculate reliability at a specific time. We can do that and let’s try it with three distributions using their respective reliability functions: exponential, Weibull, and lognormal. [Read more…]

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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…]

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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 Adam Bahret 7 Comments

Weibull explained (a bit)

Many of our customers (internal/external) trust us when we say that a Weibull analysis is the best approach to understanding what the data set is telling us. We then take their data set, do something mysterious where no one can see us, and then present these accurate predictions as to what is going to happen with a given population of the product at some future date. [Read more…]

by Fred Schenkelberg 5 Comments

Field Data Analysis First Look

Field data analysis starts with the collection of data.

In a previous article, we used a Nevada chart to gather the counts per month of field failure data. The chart also provides the necessary data to account for how many units have not failed as of yet.

The Nevada chart on its own is just a table of numbers and does not reveal patterns of the changing nature of failure rates over time. Are we experiencing early life failures or wear-out related failures?

We need to conduct some data analysis to learn what message the data contains. [Read more…]

by Fred Schenkelberg 2 Comments

Weibull Distribution

A continuous distribution is useful for modeling time to failure data. For reliability practitioners, the Weibull distribution is a versatile and powerful tool. I often fit a Weibull when first confronted with a life dataset, as it provides a reasonable fit given the flexibility provided by the distributions parameters. [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…]