Typical Tools for Particular Tolerances Table?

S

SPC_Newbie

#1
Hi All,

I've been reading a lot about (and have conducted a few) Gage R&R lately and have noticed that even in a measurement system with very good Equipment and Appraiser variaition, we can still not meet acceptable % Gage R&R numbers if the spec is tight.

Along those lines I was wondering if some general guidelines, or even a chart, exisit that correlate machine shop inspection tools with tolerances that realistically can be measured, both for product specs and statistical processes.

We have Micrometers, Calipers, Height Gages, CMM's, 2 and 3 pt bore mics and such in our precision machine shop.

Our mic's have both resolution and accuracy of .00005 inches, (Mit 293-340), Calipers .0005 resolution, accuracy?

I realize in general we want 10 units of discrimination so I probably could take resolution and mulltiply x 10? I'm thinking it's not really that simple though.

Ultimately I'm looking to have a 'good feel' for what tolerances can and can not be measured per tool on the floor reliably for SPC. Our tightest part is +.0002, -.0001. Typical tolerances are +/- .005 and our key features are commonly +.001, -0 or +0, -.001

These include ID's, OD's and lenght & width.

I hope this makes sense and seems like a reasonable question - Thanks!
 
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Michael_M

Trusted Information Resource
#2
I am posting my reply as I 'think' I understand the requirement and if I post and am right or wrong I will find out.

If you are using 10x as your standard and are measuring a +/-.005 tolerance you have a total of .010 tolerance so the instrument needs to be able to accurately read .001 or better. Your tightest tolerance is +.0002/-.0001 leaves .0003 total tolerance so you need an instrument that can accurately read .00003.

Again, I am not absolutly sure on this myself, but this is my understanding.
 

Rameshwar25

Quite Involved in Discussions
#3
Dear
Once you have selected right instrument for measurement i.e. with a least count of at least one tenth of tolerance, there are no chances your %GRR will not come below 10%. Sometimes, the range of three readings (assuming 3 trials), goes beyond UCLr, which can be seen in Range chart. If you re-check those observations and range of three readings comes within UCLr, your GRR% will be definitely come below 10%.

regards
rameshwar
 
S

SPC_Newbie

#4
Michael - thanks for the reply, it's nice to see those 'getting involved' (like myself too!) taking a stab at it!

Rameshwar25 - Thank you also - That is an intersting assertion I have not had time to think through. I do however have some data that doesn't 'appear' to agree - of course it could be that I've messed up somewhere else.

I'm attaching what I've got. Maybe this part of the thread should be posted elsewhere as intuitivly I feel my Mic and the differences in results between (and within) operators SHOULD have been more than sufficient to measure a tolerance spread of .001.

Can anyone explain WHY I failed when 'it feels' like I should have been ok?
Thanks!!

(Please ignore stability and linearity tabs as they just have data from the original spreadsheet)
 

Attachments

Rameshwar25

Quite Involved in Discussions
#5
In s0me cases, your readings are in 5 decimal digits. e.g third trial of first appraiser for first part. May I know which instrument has been used in measurement? and what is the least count?

Rameshwar
 
N

NumberCruncher

#6
Hi SPC_Newbie

Plot your results. Only sample 2 is clearly different to the others. With all of the other results, the total within sample variation as measured by your appraisers, is very large compared to the between sample variation. I don't have my GRR sheets immediately available, so I can't calculate the results from your data.

I will repeat this. Plot your data. Everything will become much clearer.

The ideal graph would show each sample with the spread of measurements. Each group of measurements would not overlap with the others in any way.

With your results, you can put a ruler through 5 of the 6 sets of data. Either you don't have enough variation in your parts, or your gauges do not have sufficient resolution.

NC
 
S

SPC_Newbie

#7
Hi Rameshwar25,

They should all be 5 digits. The 5th got left off whenever it was a zero. I used a micrometer with both .00005 inch resolution and accuracy (Mit 293-340).
 
S

SPC_Newbie

#8
Hello NC,

Thanks for taking the time to review my data and respond! I misread my xbar r by operator chart - it kind of looked like some 'R chart by operator' graphs so I thought it was close to OK. Upon review I see I don't have 50% of the points out of control.

I don't have enough variation in the parts as they are running very near the LSL with sample 2 a little too low but these are the parts that we are producing in our precision machine shop. Maybe I'm running into issues with what should be non uniform data??

If I don't have more variation among the parts am I in trouble as far as running a GR&R goes? Some notes I have say that for product acceptance 'Part Variation is not part of the calculations so ranges need not be spread across the tol range.' As far as for statistical purposes (SPC) my notes only say 'std dev of selected parts should match std dev of process when practical'. These notes are my interpretation of what Miner says is nec for part selection in 5a of his Intro to MSA series.

I chose this part and dimension because the spec tolerance range was .001 and it was easy to get a mic on it and I wanted to see what kind of numbers GR&R wise we would get. I have done GR&R before but only from a 'fill out the spreadsheet' perspective as a test engineer. Now I'm at a new company and a first time QE and need to really understand MSA.
Thank you!!
 
N

NumberCruncher

#9
Hi SPC_Newbie

GRR is really simple. "Can you measure what you are making?"

As I said in my previous post, I don't have access to my GRR sheets at the moment, so I can't give you a quantitative answer to the above question.

But if your sheets are telling you correctly that the %GRR is poor and the NDC (number of distinct categories) is less than 5, then the study hasn't failed. It's done it's job correctly. It's telling you, "No, you can't measure what you are making."

If all you need to do is weed out the odd elephant from the mice (a truly surreal metaphor!!) then this is ok. You can detect big changes.

If these parts are truly representative of your process, and you need to detect small changes in the output, you probably need a better measurement system.

This new measurement system might only involve operator training to reduce the between-operator variability. It might involve new equipment.

But here, we're getting into territory that is outside of the GRR study. Before making any expensive decisions, you need to be totally confident that your study is good. It would be more than a little embarrassing to make expensive, wholesale changes to your systems only to find that your initial study was flawed in some way.

Arguing that, someone on the internet looked at graphs of the data and said the measurement system was rubbish, probably won't work as a defence.

I will say it again, I have not analysed your data. I have just looked at the graphs and I can see that there is a lot of overlap in the data.

You need to decided if your data is a true representation of the measurement system, then make the appropriate decision. Look before you leap, said the hedgehog...

NC
 
Last edited by a moderator:
H

Hodgepodge

#10
SPC Noob

Check out this indicating micrometer. .000050" increments & IP54 coolant proof. The micrometer's gaging pressure will be constant, removing the operator controlled gaging pressure variable. The micrometer you are using is a great gage, but I would use an indicating micrometer for .0020" or less tolerance when possible.
 
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