Capability Study => Check %Study Variance and NDC?

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#1
Hello!

Our primary target is to achieve the acceptance limit of % Tolerance while we are using our measuring equipments for product control situations.
We are also using the m.equipment for cap.studies but i dont think we are using SPC. Here come my question?

Do we also have to analyse % Study Var and Ndc from the MSA result and acieve the acceptance limits for those parameters also?

Thanks in advance!
 
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Miner

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#2
Re: Capability study => check %Study Var and Ndc?

% Tolerance should be used for inspection devices.

%Study Variation (or preferably % Process Variation) and ndc should be used for the following situations:
  • SPC
  • Capability studies
  • Any statistical studies such as hypothesis tests, DOEs, etc.
 
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#3
Re: Capability study => check %Study Var and Ndc?

Interesting, so that means that we have to also has to focus on % Study Var & Ndc.
What we can see from result from MSA for a measuring equipment is that we do not achieve acceptance limits on those parameters. So this means that we have to invest in another measuring equipment if we should go on we our cap. studies. But i have to say that % Tolerance is acceptable. How do we priority this, achieve % Tolerance or % Study Var /Ndc? Any experience of that?
 
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#4
Re: Capability study => check %Study Var and Ndc?

Perhaps i rephrase my question
We use a m.equipment for product control and process control and lets say that we have following result:
% Tolerance acceptable, % Study var: 36 % and ndc : 2. We can not improve the result more. How do we proceed from here?
We can still use it for product control e.i. secure that no parts is out of tolerance limits. We can not use m.equipment for cap.studies so we can not control our process.
I see only two alterantives: new m.equipment or measure every parts .e.i. 100 % (frequency)
Am i wrong in my conclusions?
 

Miner

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#5
New equipment is definitely one option. Another option that is not highly desirable, but does work is to take the average of multiple measurements as a single measurement.

The standard deviation of a group of averages = the standard deviation of the individual measurements divided by the square root of the sample size. Therefore, if you take the average of 4 measurements as a single measurement, you will cut your measurement variation in half. This is not a great alternative, but I have been forced to use it for short term studies on occasion.
 
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#6
New equipment is definitely one option. Another option that is not highly desirable, but does work is to take the average of multiple measurements as a single measurement.

The standard deviation of a group of averages = the standard deviation of the individual measurements divided by the square root of the sample size. Therefore, if you take the average of 4 measurements as a single measurement, you will cut your measurement variation in half. This is not a great alternative, but I have been forced to use it for short term studies on occasion.
So concerning process control i.e cap.studies, you mean that in cap. studies we take the average of multiple measurements as single measurement? As you wrote this could be a temporary solution but it is quite time consuming to do cap. Studies then. 50 measuremtns will results in 200 is that correct? In this example , how will this influence our cap.study? Is there any formula we can use to show other colleagues that if we go on with our cap.studies but instead of 50 measurements we do 200 that will in theory improve the cap.index?
 
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Miner

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#7
Your understanding is correct, but I was only suggesting it for SPC purposes. The impact on the results of a capability study would be real, but relatively small.
 
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#8
But with a % Study Var of 36 % it will have an impact on our cap.studies and if we keep on doing cap.studies the result will not be realistic. So from cap.study point of view, we should immediately stop doing them? Focus on new equipment instead? Or can we go around the problem?
 
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