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→
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?→
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.
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.
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.
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.
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?→
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→
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.
By it’s cover no doubt. The title and cover are important, this is true. When you judge a reliability book we often first see and evaluate the cover.
The author? Do you buy the book based on who wrote or edited it?
Do you have a quick scan or check for key features before you add the book to your library? I’m curious how you select a book to use a reference for your work. The books we read and use for work shape our work, thus it’s important to have the right works at our disposal. Continue reading How to Judge a Reliability Book→
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.