Your Reliability Engineering Professional Development Site
Now for something completely different. Roaming the net looking for an interesting advertisement or data sheet with a ‘great’ (i.e. bad) example of the mis use of MTBF, ran across that MTBF is actually being used by at least one government for department budgeting.
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Most of us have seen reliability specified using a requirement like the following:
The Zeus 5000 SUV shall have an MTBF of 144,269.5 miles with a 90% confidence.
Some readers may not have seen reliability requirements specified in any other way. What they have always seen has read something like: The widget shall have an MTBF of X with a Y% confidence. This reliability requirement structure is rather ubiquitousin military and aerospace specifications, which along with Mil-HDBK-217, have been major influences in reliability specification practices for decades in many industries.
After a discussion with a client this morning, and their motor vendor’s reliability engineer asked for a reference for a sample size calculation formula I recommended, I had a short email exchange with said reliability engineer. In my note with the references, I included an aside with a link to this site. He liked the site and agreed that MTBF was often misunderstood and not useful. He asked if the store sold much in the way of NoMTBF logo’ed merchandise – it doesn’t btw. I thought about how and why this site and the store exist and that invited my passion on this topic once again.
We need to do something to further the eradication of MTBF.
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[updated January 2025]
Just answered a question on where to find reliability engineering training on basics and statistics. There are plenty of options and below I’m listing just where to find the many, many options available to you.
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Just back from the Reliability and Maintainability Symposium and not happy. While there are signs, a proudly worn button, regular mentions of progress and support, we still talk about reliability using MTBF too often. We need to avoid MTBF actively, no, I mean aggressively.
Let’s get the message out there concerning the folly of using MTBF as a surrogate to discuss reliability. We need to work relentlessly to avoid MTBF in all occasions.
Teaching reliability statistics does not require the teaching of MTBF.
Describing product reliability performance does not benefit by using MTBF.
Creating reliability predictions that create MTBF values doesn’t make sense in most if not all cases. [Read more…]
MTBF use and thinking is still rampant. It affects how our peers and colleagues approach solving problems.
There is a full range of problems that come from using MTBF, yet how do you spot the signs of MTBF thinking even when MTBF is not mentioned? Let’s explore the approaches that you can use to ferret out MTBF thinking and move your organization toward making informed decisions concerning reliability. [Read more…]
Over 20 years ago the Assistant Secretary of the Army directed the Army to not use MIL HBK 217 in a request for proposals, even for guidance. Exceptions, by waiver only.
217 is still around and routinely called out. That is a lot of waivers.
Why is 217 and other parts count database prediction packages still in use? Let’s explore the memo a bit more, plus ponder what is maintaining the popularity of 217 and ilk.
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This is a question someone posted to Quora and the system prompted me to answer it, which I did.
This question is part of the general question around which software tools do you use for specific situations. First, my response to the question. [Read more…]
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? [Read more…]
Thanks to a reader that noticed my question on why MTBF came into existence, we have a new (new to me at least) rationale for using MTBF. Basically, MTBF provides clarity on the magnitude of a number, because a number in scientific notation is potentially confusing.
What is doubly concerning is the use of MTTF failure rate values in ISO standards dealing with system safety.
Let’s explore the brief email exchange and my thoughts. [Read more…]
Guest post by Msc Teofilo Cortizo
The term MTBF (Mean Time Between Failures) within maintenance management, it is the most important KPI after Physical Availability. Unlike MTTF (Mean Time To Failure), which relates directly to available equipment time, MTBF also adds up the time spent inside a repair. That is, it starts its count from a certain failure and only stops its counter when this fault was remedied, started and repeated itself again. According to ISO 12849: 2013, this indicator can only be used for repairable equipment, and MTTF is the equivalent of non-repairable equipment. [Read more…]
Reliability activities serve one purpose: to support better decision making.
That is all it does. Reliability work may reveal design weaknesses, which we can decide to address. Reliability work may estimate the longevity of a device, allowing decisions when compared to objectives for reliability.
Creating a report that no one reads is not the purpose of reliability. Running a test or analysis to simply ‘do reliability’ is not helpful to anyone. Anything with MTBF involved … well, you know how I feel about that. [Read more…]
Three prototypes survive the gauntlet of stresses and none fail. That is great news, or is it? No failure testing is what I call success testing.
We often want to create a design that is successful, therefore enjoying successful testing results, I.e. No failures means we are successful, right?
Another aspect of success testing is in pass/fail type testing we can minimize the sample size by planning for all prototypes passing the test. If we plan on running the test till we have a failure or two, we need more samples. While it improves the statistics of the results, we have to spend more to achieve the results. We nearly always have limited resources for testing.
Let’s take a closer look at success testing and some of the issues you should consider before planning your next success test. [Read more…]
The following note and question appear in my email the other day. I had given the definition of reliability quite a bit of thought, yet have not really thought too much about a definition of ‘product life time’.
So after answering Najib’s question I thought it may make a good conversation starter here. Give it a quite read, and add how you would answer the questions Najib poses. [Read more…]
Here’s a common problem: You have been tasked with peering into the future to predict when the next failure will occur.
Predictions are tough.
One way to approach this problem is to analyze the history of failures of the most typical system. The issue looms larger when you have only two observed failures from the population of systems in question.
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 readers 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. [Read more…]