Attribute MSA for Visual Inspection via Camera Automatic Inspection Tool

B

Bobbinz

#1
Hey guys,

I'm sure this must have been asked more than once so apologies in advance if the answer is already available - I just haven't yet been able to find it.

I have a tool that inspects parts for defects. The tool can take up to 10 parts at a time, then inspects each one separately and fails any parts which contain a defect (visual inspection via camera) The parts can only be loaded once, after output it is not possible to load them into the input. However, once they are loaded, I can pass them under the inspection camera as many times as I need to.

As the inspection is a control, it needs to have MSA carried out. I was initially thinking of using Kappa analysis, but as I can only inspect 10 parts for the study, it feels as though there won't be enough data for reliable results. For example, I can run the 10 loaded parts twice round the system and record the pass/fail result for each pass per part. This always returns 100% K score. It just doesn't feel right - in production, the tool processes ~8000 parts per hour, so the 10 parts I load is not really fully representative of the product.

Can anyone offer some advice on a suitable MSA method for this?

Many thanks for reading.
BBz
 
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bobdoering

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#2
The key is to have parts in the "gray" area - nearly good or bad - not obvious good and bad parts. For attribute, it is the specimens that are key to the value of the test.
 
B

Bobbinz

#3
Ok, thanks for the reply. Presumably then, the two passes of ten samples is enough with the right samples? With it being a defect inspection tool, processing thousands of devices per hour, it is extremely difficult to identify ten borderline devices. Furthermore, any manual handling of identified candidates has the high risk of being compromised, thus rendering the sample useless. Manual addition of defects generally results in extreme examples rather than borderline.

BBz
 

Bev D

Heretical Statistician
Staff member
Super Moderator
#4
10 parts will most likely not be enough. However, can't you do multiple sets of 10? 10 today, 10 tomorrow, etc.?

That said, I have posted a document entitled “MEASUREMENT SYSTEMS VERIFICATION AND VALIDATION” . ***DEAD LINK REMOVED***

The document includes both continuous data and categorical data measurement systems...and will help you structure your MSA appropriately.
 
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B

Bobbinz

#5
Hi Bev,
The document that you posted specifies that for Kappa, a score >= 0.95 is required. Is this value your own locally agreed figure? If not, where does it come from? MSA4 (p137, pdf) implies that > 0.75 is considered "good to excellent agreement", and is presumably the level expected by any industry adopting the said standard?

Thanks for your advice
BBz
 

Bev D

Heretical Statistician
Staff member
Super Moderator
#6
K>0.95 is locally agreed upon, but is also just plain common sense.
Think about it for a minute: a K=0.75 roughly means that you get only 75% agreement...that's a LOT of false rejections, false acceptances or disagreemeng among inspectors: can you afford that?

In my organization we actually set a false accept/reject rate that is tolerable based on the nature of the defect, the rework, scrap or customer return cost and the effect on the customer if it were to escape to the field. In some cases the rate may be far less than 5% or even greater if it is a trivial defect. The K>0.95 is just a rule of thumb.

We must always take these statistical lines in the sand that are published in any standard with a large grain of sand. There is no substitute for thinking about adn understanding your specific situation and it's needs.
 
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