Considerations When You Calculate MTBF

It is deceptively easy to calculate MTBF given a count of failures and an estimate of operating hours. Just tally up the total hours the various systems operate and divide by the number of failures. Easy.

This simple calculation is the unbiased estimator for the inverse of the parameter lambda for the exponential distribution, or directly to estimate theta (MTBF). We use theta to represent 1 / lambda.

What could go wrong with such a simple calculation? [Read more…]

How do you know? How would you know?

There is a lot to know concerning the technical aspects of reliability engineering. From calculating summary statistics to discovering the root cause of a failure, the body of knowledge you should master as a reliability professional is expansive. [Read more…]

We gather and report loads of data nearly every day.

Is your data “good data”? Or does it fall into the “bad data” category?

Let’s define the difference between good and bad data. Good data is accurate, timely, and useful. Bad data is not. It may be time to look at each set of data you are collecting or reviewing and judge if it’s good or not. Then set plans in motion to minimize the presence of bad data in your organization. [Read more…]

This one made me scratch my head and wonder. Did I read this right?

A reader sent me an excerpt of a document found on Vicor’s site.

“Reliability is quantified as MTBF (Mean Time Between Failures) for repairable product and MTTF (Mean Time To Failure) for non-repairable product. A correct understanding of MTBF is important. A power supply with an MTBF of 40,000 hours does not mean that the power supply should last for an average of 40,000 hours. According to the theory behind the statistics of confidence intervals, the statistical average becomes the true average as the number of samples increase. An MTBF of 40,000 hours, or 1 year for 1 module, becomes 40,000/2 for two modules and 40,000/4 for four modules…”

[Read more…]

Recently heard from a reader of NoMTBF. She wondered about a supplier’s argument that they meet the reliability or MTBF requirements. She was right to wonder.

Estimating reliability performance a new design is difficult.

There are good and better practice to justify claims about future reliability performance. Likewise, there are just plain poor approaches, too. Plus there are approaches that should never be used.

[Read more…]

Why Do Reliability Testing

Reliability testing is expensive. The results are often not conclusive.

Yet we spend billions on environmental, accelerated, growth, step stress and other types of reliability tests. We bake, shake, rattle and roll prototypes and production units alike. We examine the collected data in hopes of glimpsing the future. [Read more…]

Formal education (master’s or Ph.D) or design/manufacturing engineering experience?

Where do you look when hiring a new reliability engineer? Do you head to U of Maryland or other university reliability program to recruit the top talent? Or, do you promote/assign from within? Where do yo find the best reliability people? [Read more…]

Accelerated Testing: Statistical Models, Test Plans, and Data Analyses by Wayne Nelson

Published by John Wiley & Sons in 1990 this 601 page book started my career in reliability engineering.

I didn’t know it at the time in the early ‘90s, yet my assigned task to create an accelerated test for a new product would spark an interest in cheating time. Wayne’s book helped make that first accelerated test successful.

The Accelerated Testing book is a compendium of different ways to conduct accelerate tests with a focus on the planning the test and analyzing the data. Wayne is a reliability statistician, and as he will tell you, not an engineer. Thus the book tends to focus on the math.

What I enjoy about the book is the math is not the dry academic derivation driven material, it is full of examples and immediately useful formulas. There is just enough explanation to help the math wonks pursue their interest, and enough practical information to allow engineers to develop and conduct meaningful experiments. [Read more…]

Neither includes using MTBF, btw.

And, I’m not thinking about the common language definition either.

Plus, I may have this all wrong. Here is the way I think about the reliability of something. More than ‘it should just work’ and different than ‘one can count on it to start’. When I ask someone how reliable a product is, this is what I mean.

By explaining my basic understanding we can compare notes. It is possible, quite possible, that I will learn something. As you may as well. Let’s see. [Read more…]

The Damage Done by Drenick’s Theorem

Have you ever wondered by we use the assumption of a constant failure rate? Or considered why we assume our system is ‘in the flat part of the curve [bathtub curve]’?

Where did this silliness first arise?

In part, I lay blame on Mil Hdbk 217 and parts count prediction practices. Yet, there is a theoretical support for the notion that for large, complex systems the overall system time to failure will approach an exponential distribution.

Thanks go to Wally Tubell Jr., a professor of systems engineering and test. He recently sent me his analysis of Drenick’s theorem and it’s connection to the notion of a flat section of a bathtub curve.

Wally did a little research and found the theorem lacking for practical use. I agree and will explain below. [Read more…]

3 MTBF Stories

Everyone loves a great story. Storytelling has been a long tradition to pass along knowledge and wisdom.

There are good stories, tales of inspiration. There are sad stories, tales of caution.

There are fables, ghost stores, legends, epic poems, and more. When considering the reliability performance of your product or equipment, you probably have a few stories that you can tell. “That time … “

Simple join colleagues for lunch and ask about the ‘major disasters’ of the past. The stories help us to remember and hopefully avoid repeating mistakes.

Here are three stories with MTBF as a central figure. It is a site and blog that does take about MTBF, so it fits. To start, let me introduce you to Martin, a new reliability engineering reporting to his first day of work at a bicycle design and manufacturing company. Two sad stories and a good one. enjoy. [Read more…]

Trying to Respond to All Questions and Comments Concerning MTBF

Over the past couple of days, like most days, have received questions and comments concerning MTBF. I do try to respond to all questions and acknowledge the comments.

Glad to help in anyway I can, so please feel free to send me your questions. Certainly do appreciate the supporting comments, or any comments for that matter.

Let’s take a look a few such discussion that occurred over the past two days. [Read more…]

How We Think About Reliability Is Important

Getting on an airplane we think about the very low probability of failure during the flight duration. This is how we think about reliability.

When buying a car we think about if the vehicle will leave us stranded along a deserted stretch of highway. When buy light bulbs for the hard to reach fixtures we consider paying a bit more to avoid having to drag out the ladder as often.

When we consider reliability as a customer does, we think about the possibility of failure over some duration.

And, we really don’t like it when something fails sooner than expected (or upon installation). [Read more…]

Is MTBF Preventing Your Product From Being Reliable?

MTBF is not reliability. Attaining a specific MTBF does not mean your product is reliable. MTBF use may be the culprit.

Therefore, working to achieve a MTBF value may actually be preventing you from creating a product that mets your customer’s reliability performance expectations.

Actively working to achieve MTBF using the common tools around MTBF may be taking you and your team down the wrong rabbit hole. You may be working to reduce the reliability of your products rather than improving them.

Let’s take a look at a couple of ways the pursuit of MTBF is harmful to your product’s reliability potential and contrary to your customer’s expectations. [Read more…]