True Progress

This article recently brought up an excellent point on how some rates can be deceiving, and even reduce the likelihood that we will make the right decision. The example involved comparing impressions of fuel efficiency in miles per gallon versus gallons per mile, or gallons per ten thousand miles. While identifying the better of two options in either case is easy regardless of the rate, other types of evaluations can be much more complex if we end up using the wrong units. Read the rest of this entry »

Often as a reliability engineer, or anyone responsible for researching the reliability of an item, or calculating it, you will find oversimplified published data giving you the impression that reliability is an unchanging physical property like mass or volume, something intrinsic to the materials included in it. This is actually the common sense approach; we know an old thing is less reliable than a new copy of the same thing. But, this common sense gets argued out of us when we are faced with reconciling tables of MTBF (mean time between failures) values, nines (i.e. 0.99999, a measure of reliability), failure rates and other things. Let’s get back to the common sense approach, but with math. Read the rest of this entry »

So, you’ve got a design that you want to prove is better than the existing design from your own or another company. What’s the most efficient, fastest way to get to that answer with a very small sample size? Whle there may be several options you have, including accelerated testing, they each can have their benefits and drawbacks. Here, I will advocate for zero-failure testing as a realistic and useful option, especially since it is something we often do anyways, but without the mathematical justification. Read the rest of this entry »

Getting answers before you are finished. Why are people always so impatient? Why can’t they just wait until testing is complete before they ask for answers? I suppose it is just human nature, as I have heard that question any time I have been involved in reliability testing programs. And, although we would know much more if we waited for more data to roll in, there are times that we can evaluate where our project stands on the basis of partial test results. Read the rest of this entry »

As a reliability analyst, sometimes none of your data matches the form you are interested in. It all comes in different collections of units, statistical distribution parameters, failure rates, environments, MTBF, MTTF, and on and on. In this article, let’s consider one common conversion for which my research found too little information available on the internet. Read the rest of this entry »

True-Progress.com has released its Free Weibull Reliability Calculator version 1.0.2.

You can download this tool by following this link.

This simple calculator utilizes the Weibull distribution to generate reliability data for your system Read the rest of this entry »