Cpk vs Ppk: shortterm vs longterm process variation
Ғылым және технология
When calculating SPC control limits, many find out that even the data they use to calculate those limits already breaks rules within that same reference period. That shouldn't be possible, right? Standard deviation calculations tend to estimate wider variation than what's observed in the sample data.
Well, it is. And it's because of how sigma is estimated: not by calculating the standard deviation over the whole sample, but by estimating it based on the average (moving) range observed.
The same happens with Cpk vs Ppk - with Cpk using that same estimation from range and Ppk calculating over all values in the data set.
That is by design, though, because for SPC and Cpk you want to know short-term variation and specifically try to differentiate between everyday process variations and real process shifts.
#continuousimprovement #sixsigma #spc
Пікірлер: 9
Very perfectly explained , Looking forward for such more contents in a world where we only see theoretical or bookish explainations.
@TomMentink
Жыл бұрын
Thanks for your kind words - I'm happy to hear that you like my approach to our topic
Great lesson. It took me some time to fully get it, but I eventually got there! This topic is not really very often addressed in a technical way like shown in the video. Tom, you clarified everything. Thank you!
@TomMentink
Жыл бұрын
I feel you - this is a tricky thing to grasp. I'm also not a big statistics buff myself, but find that when I understand what the statistics are trying to do/prove, it becomes much easier to understand the maths it uses. Glad to hear that this video helped your understanding too.
@domenicoscarpino3715
Жыл бұрын
@@TomMentink absolutely! Thanks again Tom
Hi Tom, i have seen a scenario where If PP and PPK fail to achieve the minimum requirement e.g. 1.67 but CP and CPK passes. The big factor is the tolerance is so small it doesn't leave much room for any process variation as PP and PPK is long term. What are your thoughts on this due to tight tolerances?
@TomMentink
Ай бұрын
When Cpk is good, but Ppk is not fully up to your demands (Ppk 1.67 is pretty high, mind you), that means your process' average is shifting over time. Maybe there are large and unpredictable differences between material batches, which influences your process outcome, but most other factors should be controllable (not per se easy to control, but that's what you should work on). In a more recent video, I also explained why I think that for many industries, Cmk >1,67 Cpk >1,33 and Ppk >1,00 is sufficient. You might want to up all of them by 0,33 for more demanding customers, but the tolerances you place on your system do indeed seem very strict. kzread.info/dash/bejne/eJ1qubJ8l9rOoMo.html
Please be careful with you language as you explain these statistics. ppk 1 is not "horrible".. its likes a 0.1% scrap rate which depending on the situation can be EXCELLENT... you also generalize long term short term as "today" vs the "whole year". This can lead to misconceptions and conclusions from your audience.
@TomMentink
2 ай бұрын
You’re right, there is a lot more nuance with these studies, and I take a couple liberties to get the general concept across. I try to balance precision with easy to understand, which is a balance that will never be right for everyone. On Ppk of 1 being horrible, I agree with you - that was an overstatement: Ppk of 1 to 1,3 is good enough. Thanks for that correction.