Futility of Using MTBF to Design an ALT
Let’s say we want to characterize the reliability performance of a vendor’s device. We’re considering including the device within our system, if and only if, it will survive 5 years reasonably well.
The vendor’s data sheet lists an MTBF value of 200,000 hours. A call to the vendor and search of their site doesn’t reveal any additional reliability information. MTBF is all we have.
We don’t trust it. Which is wise.
Now we want to run an ALT to estimate a time to failure distribution for the device. The intent is to use an acceleration model to accelerate the testing and a time to failure model to adjust to our various expected use conditions.
Given the device, a small interface module with a few buttons, electronics, a display and enclosure, and the data sheet with MTBF, how can we design a meaningful ALT? Continue reading Futility of Using MTBF to Design an ALT
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. Continue reading The Damage Done by Drenick’s Theorem
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. Continue reading 3 MTBF Stories
Different Data Same Decision
Let say you have some time to failure data on your equipment. A common action is to calculate the MTBF. All well and good until you expect to make a meaningful decision based on the calculation.
Using just the mean of the data, the MTBF value is likely to provide you with a less than useful bit of information. Thus your decision will be rather random or worthless.
Let’s explore just how this simple calculation of perfectly good data can mislead your decision making. Continue reading Different Data Same Decision
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? Continue reading How About Weibull Instead of MTBF?
Let’s Demand Better Reliability Engineering Content
Teaching reliability occurs through textbooks, technical papers, peers, mentors, and courses. The many sources available tend to use MTBF as a primary vehicle to describe system reliability.
What has gone wrong with our education process? Continue reading Are We Teaching Reliability All Wrong?
Life Data Analysis with only 2 Failures
Here’s a common problem. You have been tasked to peer into the future to predict when the next failure will occur.
Predictions are tough.
One way to approach this problem is to do a little analysis of the history of failures of the commonest or system. The problem looms larger when you have only two observed failures from the population of systems in questions.
While you can fit a straight line to two failures and account for all the systems that operated without failure, it is not very satisfactory. It is at best a crude estimate.
Let’s not consider calculating MTBF. That would not provide useful information as regular reader already know. So what can you do given just two failures to create a meaningful estimate of future failures? Let’s explore a couple of options. Continue reading Life Data Analysis with only 2 Failures
The Importance of the Discussions around MTBF Questions
The best way to help others understand and stop using MTBF is to engage them in a discussion. I get questions concerning MTBF or reliability a few times a week. I attempt to answer each and every one, plus adding a follow up question or two.
In person or online, ask and answer MTBF questions. You not only improve your understanding of MTBF and reliability, you improve your still at tell stories to help affect change across your industry. Continue reading Discussions and MTBF Questions
The MTBF Stories You Tell Can Cause Change
Stories communicate well. We have been telling stories long before the invention of writing, or the internet. The MTBF stories we tell communicate our ideas, suggestions, and recommendations.
There are a differences between good and poor stories. How you tell a story matters as well as the subject of the story. Now, MTBF stories may not be the most thrilling or entertaining, yet there are stories on MTBF topics that matter.
Let’s explore using the power of story to cause those around us to better understand and avoid the use of MTBF. Continue reading 3 Types of MTBF Stories
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. Continue reading 3 Recent Questions and Comments Concerning MTBF
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). Continue reading How We Think About Reliability
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. Continue reading MTBF Use May Reduce Product Reliability
When Asking for Reliability Information Do You Ask for MTBF?
Our customers, suppliers, and peers seem to confuse reliability information with MTBF. Why is that?
Is it a convenient shorthand? Maybe I’m the one confused, may those asking or expecting MTBF really want to use an inverse of a failure rate. Maybe they are not interested in reliability.
MTBF is in military standards. It is in textbooks and journals and component data sheets. MTBF is prevalent.
If one wants to use an inverse simple average to represent the information desired, maybe I have been asking for the wrong information. Given the number of references and formulas using MTBF, from availability to spares stocking, maybe asking for MTBF is because it is necessary for all these other uses. Continue reading How Did Reliabilty Become Confused with MTBF?
What Price Providing MTBF?
If your livelihood consists of providing MTBF upon request, what good is your service?
Sure you earn some money, yet did the customer receive value in the transaction? As you know, or should know, MTBF is so commonly misunderstood that it is likely the customer confused what they want, reliability, with MTBF. Providing them MTBF does not answer their question.
Worse the customer thinks they got something of value and blithely heads off with rather meaningless information.
My contention is by providing MTBF because customer’s request it is wrong. We know better. Those performing predictions, doing data analysis, and other reliability engineering work know that MTBF is a faulty and rather meaningless metric often confused with reliability, R(t). (probability of success over a duration). Continue reading The Business of Providing MTBF
Let me ask you something concerning MTBF
Do make compromises around gathering and analyzing data since you only need to report MTBF?
Do you use MTBF (exponential distribution) based test planning when you know the product has a non-constant hazard rate?
These questions came up this week via email looking for advice when directed to ignore the actual situation and just do what the customer wants.
I’m traveling this week, rather jet-lagged today, so going to keep this one short.
How would you answer these questions? What advice would you give someone using exponential based reporting, test planning, or data analysis approaches knowing the customer expects that process yet the data and your experience suggest you should use another method (Weibull or MCF, for example)?
Please add you comments below and let’s prepare a list of what one should say or use to respond to such actions.