Your Reliability Engineering Professional Development Site
A series of articles devoted to the eradication of the misuse of MTBF.
ISSN 2168-4375
Plus, we explore other commonly misused or misunderstood reliability-related topics and what one should do instead. A little understanding will help you get better results with your efforts.
Note: This is a reposting with editing, updating, etc. of the articles that first appeared at NoMTBF.com.
My first question, which I generally keep to myself, is ‘MTBF, yeah, right. Do they know better or not?” This is generally not a good way to start a conversation with a vendor about the reliability information you need to make appropriate decisions. [Read more…]
We talk about reliability because it matters. The ability to estimate reliability allows us to make design and development decisions. The ability to monitor reliability allows us to adjust the design, suppliers or expectations about a product. [Read more…]
The math would be easier.
The exponential distribution would be the only time to failure distribution. We wouldn’t need Weibull or other complex multi-parameter models. Knowing the failure rate for an hour would be all we would need to know, over any time frame.
Sample size and test planning would be simpler. Just run the samples at hand long enough to accumulate enough hours to provide a reasonable estimate for the failure rate. [Read more…]
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…]
The acronym MTBF is commonly known in our field as “Mean Time Between Failures”.
It is also associated with repairable systems in most textbooks.
It is also denoted as the theta parameter for an exponential distribution.
It is also referenced as a metric for reliability. Oh, and it is the inverse of the failure rate.
And, it is misunderstood and misused by many. I digress, as there is plenty already written on the Perils of MTBF.
What is MTBF? And where and how should it be used, if at all? [Read more…]
Did you know I was interviewed for the Dare to Know podcast? The interview was fun, check it out here.
Note: this interview was some time ago (about 10 years back), near the start of the article series called NoMTBF. My thoughts haven’t changed very much. Plus, it seems this campaign is slowly working across our profession.
Learning the basics of reliability engineering is where we all start. Mastering the range of skills and techniques is a never-ending quest.
Improving, maintaining, and expanding your reliability engineering professional skills takes many forms. There are plenty of options and sources to support your education, yet are you getting enough of the right material? [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…”
One of the issues I’ve had with failure modes and effects analysis is the focus on failure modes.
The symptoms that the customer or end user will experience are important. If a customer detects that the product has failed, that is a failure. The FMEA process does help us to identify and focus on the important elements of a design that improve the product reliability. That is all good.
The issue is that the FMEA process doesn’t go far enough to really aid the team in focusing on what action to take when addressing a failure mode. The process does include the discussion of the causes of the failure mode. The causes are often the team members’ educated opinions on what is likely to cause the failure mode. Often the description of a cause is a failed part, faulty code, or faulty assembly.
Generally, the discussion of causes is vague.
To make informed decisions, you need information.
To form conclusions, you need evidence and a touch of logic.
To discover patterns, you need data.
In each of these cases, and others, we often start with data. The data we have on hand, or can quickly gather.
We organize data into tables, summarize data into reports, display them in dashboards, and analyze the results to inform decisions. [Read more…]
Having the technical and business skills is not sufficient to be a good reliability engineer.
You must also work with other people. With your peers, across the management team, with suppliers, contractors, and customers.
The ability to work well with others is often complex and situational. Being aware of a few basic skills will allow you to learn and improve. Prette and Prette define social competence as the social skills:
that meet the different inter-personal demands in the workplace in order to achieve the goals, preserve the well-being of the staff and respect the rights of each other.
A. Del Prette e Z. A. P. Del Prette, Psicologia das relações interpessoais: vivências para o trabalho em grupo, Vozes, Petrópolis, 2001.
Knowing how to estimate sample size or create a Weibull plot is not enough today.
Just having technical skills, while essential, is not sufficient.
Having a master of business administration (MBA) may be helpful, and it is not required; knowing the warranty and brand cost per failure is essential.
You also need to know which analysis to conduct and how it fits into the larger program and organization, plus how it impacts your customers. You also need to understand the business side of your work. [Read more…]
The fundamental technical skills, as I see it, have to include statistics and root cause analysis skills. This skill set is one of three broad areas introduced in the article, What Makes the Best Reliability Engineer?
I would say these are the minimum technical skills for a good reliability engineer. Able to calculate sample size requirements, understand a dataset, and correctly determine the root causes of a failure. [Read more…]
