All posts by Fred Schenkelberg

About Fred Schenkelberg

I am an experienced reliability engineering and management consultant with my firm FMS Reliability. My passion is working with teams to create cost-effective reliability programs that solve problems, create durable and reliable products, increase customer satisfaction, and reduce warranty costs.

AQL decision

Recently I received a question related to setting an Acceptable Quality Level (AQL) for a sampling of fielded electricity meters. The question was on how to select the right AQL for use with the sampling plan. I was not sure from the question if the sample would determine if the population would be replaced or not (expensive), or simply an experiement to determine how the meters are doing after 15 years of service (information only). Continue reading AQL decision

The MTBF Battle Continues

This site is part a long string of attempts to eradicate the improper use of MTBF. This week two people have sent me references to work previously done and Chris sent me another podcast also highlighting issues with MTBF. Jim McLinn wrote about the possible transition away from constant failure rate Continue reading The MTBF Battle Continues

Wrong Conclusions

Here is a podcast by Chris Peterson of H and H Environmental Systems which includes her thoughts on the MTBF topic. She also explores how making even ‘obvious’ assumptions may lead to the wrong conclusions.

Chris records a podcast almost everyday and many are enjoyable, fun, and and provide something to think about as you go about your day. If you like the podcast above, check out her growing list of available podcasts.

Embedded podcast with permission of Chris.

Use Lognormal Distribution

The lognormal distribution has two parameters, μ and σ. These are not the same as mean and standard deviation, which is the subject of another post, yet they do describe the distribution, including the reliability function.

\displaystyle R(t)=1-\Phi \left( \frac{\ln (t)-\mu }{\sigma } \right)

Where Φ is the standard normal cumulative distribution function, and t is time. Continue reading Use Lognormal Distribution

Where does 0.7eV come from

This post is a conversation first held on the LinkedIn group No MTBF. I’m capturing a portion of the contributions here to continue the discussion or to widen the audience. Reminds me of always assuming 95% confidence is the right value when designing a test, or assuming constant failure rate. So, let the conversation continue, starting with the original post. Continue reading Where does 0.7eV come from

Datasheet MTBF

Some many years ago I ran across a data sheet for a cooling fan (used to cool a desktop computer, for example) that listed the fan’s life as 50,000 hours MTBF. The big bold lettering was on the data sheet and was the only use of bold on the entire data sheet. One couldn’t miss it. The computers we used these fans within had a one year warranty, plus were expected to operate for a home computer user for about 5 years. Thus, we would expect the fan to also operate for five years without failure. Continue reading Datasheet MTBF

MTBF Eradication

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 Continue reading MTBF Eradication

I must not MTBF. MTBF is the mind-killer. MTBF is the little-death that brings total obliteration. I will face my MTBF. I will permit it to pass over me and through me. And when it has gone past I will turn the inner eye to see its path. Where the MTBF has gone there will be nothing. Only Reliability will remain.

  • Bene Gesserit Litany Against Fear. (with apologies)

5 Reliability Training Options

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. Continue reading 5 Reliability Training Options

Role of parts count prediction

Great note [response to comment on Drain in the Bathtub Curve on NoMTBF Linkedin Group] – yes, there is a place for parts count prediction — not to determine the mtbf, to encourage proper derating, thermal engineering, and parts reduction, etc. It’s a start and as you note only one part of the reliability program. Continue reading Role of parts count prediction

The Linkedin NoMTBF group is growing and while not very active does have an occasional interesting discussion. Join the discussion and maybe relate how you have raised awareness around the proper use of MTBF.

http://www.linkedin.com/groups/No-MTBF-1857182/about

Arrhenius or Erroneous

the following is a discussion on the sister Linkedin NoMTBF Group recently. It was and may continue to be a great discussion. Please take a look and comment on where you stand? Do you some form of the Arrhenius reaction rate equation in your reliability engineering work?Join the discussion here with a comment, or on the Linkedin group conversion.

Fred

Continue reading Arrhenius or Erroneous

An excellent short white paper by Craig Hillman that is worth reading. It underscores whey I claim HALT is the second worst 4 letter acronym in our profession. See the paper at http://www.dfrsolutions.com/uploads/white-papers/Why_HALT_Is_Not_HALT.pdf