Survey about Attribute Gage and Sight Checking R&R

N

Nixverstehikus83

#1
Hi :bigwave:,

I?m interested in making a suvery about your results for making MSA for attribute gauging and sight checking.
I think that when you introduce these MSA to your company it costs a lot of money. And if something costs a lot of money it must have a benefit.
So I?m interested in the experiences you have done in the companies.

My opinion is that a lot of people do this but at least there ist no change. For example I?ve done some R&R for sight checking. The results were like almost always the inspectors identified about 70-90% of the bad parts. But if it is the only way you can check this part (because there is no other way or because the other method is to expensive) it does not change anything.

Maybe it is possible to give a percentage number for bad attribute gauging R&R and bad sight checking MSA. And some word what does the bad results change.

Thanks... I think this survey will be interessting for other forum members too.
 
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Bev D

Heretical Statistician
Staff member
Super Moderator
#2
hmmm. I do use categorical MSAs a considerable amount of time and have realized substantial benefits. It's important to remeber that no assessment tool fixes anything. it can only quantify current state and reveal some clues about how to improve. people must do the hard work of improving systems that do not meet performance.

So you did an MSA that shows your visual inspectors only detect bad product 80-90% of the time. What actions did you take to improve their ability? That is the critical element to a successful MSA program.
 
N

Nixverstehikus83

#3
Hello,
That?s the point. I have seen some examples were they do a lot of things to improve the sight checking.
The result of the check is depending on perception and concentration of the worker. Just look on the google results for optical illusion. A human is not able to make sight checking with a zero error rate.
I don?t want to say that a human is not able to do the sight checking, in some cases there isn?t other possability. What I wan?t to say is that you might improve your sight checking up to a quote of 95%. But this ist only a snapshot. You can make 10 MSA with a very satisfaction results. One morning, the inspector comes, after an argument with his wife, to woork. And you only have bad results in your exam. Because he will not be able to concentrate. It's only human.
 
Last edited by a moderator:
P

Piotr Stoklosa

#4
That's true that attribute GRR can be beneficial. Some examples:
1) If you see that all operators have low kappa it can be a sign that your acceptance criteria are not precise.
2) If you see that operators have different kappas (for example A*B > 0.90 and B*C<0.50 and A*C<0.50) you can conlude that you have "calibration" problem with C operator.
3) If the operators have high Miss Rate your system tends to pass defective parts.
4) If the operators have high False Alarm Rate your system tends to reject good parts.
5) If you define Ref Value using expert decision then you can use the same sample set to verify training effectiveness of your new operators.

That's also true that sight control systems are very sensitive to human factor. From practice I can recomend one "soft" solution. You can allow your controlers to have a few "bad days" a year. If they have a somatic or mental problem they can report it to supervisor with no consequence: "Boss, I fill bad today. Give me less responsible work." The cost of shifting this worker to other job will be lower than the costs of wrong sight inspeciton.
 
I

iamtroll

#5
I think that the point of any MSA is improvement and discovering best practices. No measuring system is perfect, look at how the MSA is designed, it is not about getting a perfect score but understanding where your weaknesses are then trying to correct them and plan for them. Even with measuring tools there is error allowed. If your visual inspector can have a bad day, so can your tool and gage inspector. The best that you can hope for is that you identify best practices and how to spread them to all of you workers while mitigating your own systems deficiencies. The knowledge that your system is not perfect should be a driving force for improvement not an excuse for failure.
 

Bev D

Heretical Statistician
Staff member
Super Moderator
#6
The fact that no measurement system is perfect is also why it is the second thing we check for an out-of-control event.

Gages get dropped, inspectors drift and shift, temp & humidity alters gages, maintenance and calibration change instrument set points...etc.
 
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