Practical Quality Engineering Resources FMEA and the RPN 2016-01-20

Bev D submitted a new resource:

FMEA and the RPN - RPNs are mathematically incorrect, diversionary and subject to gamesmanship

Read more about this resource...

 

As Bev stated in the article, the only way to reduce Severity is to change the design. By introducing current limiting circuitry, you have changed the design and lowered the Severity.

 

Not so sure the design has been changed. Current limiting circuitry is a mitigation. If the board is still dealing with high current to function then the primary design hasn't changed. It's like an airbag in car. The circuitry can still fail and then the death hazard will be back. The circuitry reduces the probability of occurrence of death but not it's severity. To do that you would have to eliminate the need for such high current on the design. You have added a new severity of a shock with current limiting circuitry. A question to consider is why we feel the need to change a number instead of using science validation data logic and reason to understand that appropriate mitigation was taken?

 

And what is wrong with that? Are you trying to report a number that will make your management or auditor happy? do they not understand the English language or results of validation testing? (not trying to be combative, I really want to understand)

Probability scales are still fuzzy as they are still guesses and do not take into account future manufacturing problems (yours or your suppliers) that can cause the mitigation to fail. Your validation data can show that if the mitigation is applied as intended a death level shock will not occur. (we do this with centrifuges all of the time - it's in the centrifuge testing standard that. Even a metal rotor that is highly unlikely to disrupt must have it's containment tested by forcing the rotor to disrupt. If the containment mechanism works then the centrifuge is acceptable even tho the severity of the unlikely event (disruption and lack of containment) are low.

I'm not saying we shouldn't take mitigating factors into account. we absolutely should. When my organization applies mitigation we asses the severity of the mitigation if it provides residual or additional failure modes, we validate that it will work and we control it. Then we move on to the next thing...
I have seen current limiting circuitry fail due to component issues and assembly problems. when they fail, the original risk comes back. There is no way to quantitatively assess that probability.

Here's my larger point:

I suggest that our fixation on quantifying things is related to our need for a score. Our lives are surrounded by scores. Who won the super bowl? The score will tell you. Should I wear a coat or a jacket? The temperature will tell you. Who’s going to win the election? The poll numbers will tell you. Am I healthy? My blood pressure, heart rate, weight, and cholesterol numbers will tell me. Scores are simple. They are easy to communicate and easy to understand. We are told that we need data to make decisions. We accept a number at face value because we want a simple direct fast easy to understand answer. Unfortunately we accept numbers at face value. We don’t probe into the test structure; we don’t try to understand the ‘scoring method’ (formula), we don’t even look to ensure that the number wasn’t just randomly selected. It’s data; it must be correct, right? The cognitive dissonance is that even when we know the scoring method is fundamentally flawed and the resulting number has no reliable meaning we persist in calculating it, reporting it and making decisions based on it. Because it’s a number. And we want it to work. Because it’s a number. Numbers aren’t subjective right? They are precise. They are exact. They are data. Deming said: Some things that can be counted don’t matter and some things that matter can’t be counted. We need to learn that difference.