Please clarify the Rule of 10 to 1 - AND - What is the ndc number?

I am receiving a lot of good input here and it is very appreciated - unfortunalty it also brings up more questions...

I'll start at the begining...
I understand that the standard uncertainty for wringing is 0.00005" and that when you stack up the tollerances you come up with 0.00015". I get a little lost at the next step - How do you determine the rectangular distribution vs. Square or triangle?

Now, take several readings, get standard deviation, divide by n-1 to obtain Type A or random uncertainty and drop into the final formula.....

I don't really understand any of this other than the fact that Type A is the random uncertainty and Type B is the Systematic uncertainty...

Then take the Student T-Tables to multiply to achieve 95% confidence.....in theory, one can determine specific degrees of freedom, but in a practical approach the Type B contributions (which have no set number) are considered infinite and so 1.96 will provide 95% confidence.....but the confidence is typically expressed at k=2 which arrives at 95.5% confidence, but is easier to work with.....

This is also a little confusing for me - If you could break down these steps a little for me that would probably help a lot - or perhaps point me to the correct reference material that explains what is happening here...

As I said I am struggling with uncertainty - mostly because no one here where i work knows what it is and I can't seem to get them to send me to a class - I just have to figure it out all on my own (not a very envious position to be in I know...) along with the help of all of the people here of course.

I must say that in the last 6 months I have been trying to learn and impliment the requirements of ISO 17025 I have learned quite a lot so please don't give up on me...

Could anyone pls explain about variable MSA, i keep doing this using long method but still can't get ndc more than 5. Is it mean my equipment is not suitable?
is tolerence of part may effect the result?

airaza08 said:

Could anyone pls explain about variable MSA, i keep doing this using long method but still can't get ndc more than 5. Is it mean my equipment is not suitable?
is tolerence of part may effect the result?

Click to expand...

There have been a lot of discussions here on the ndc value.
A search in this forum ( maybe best started at the bottom of this page here - similar discussion threads ) will shine a light on this.

ndc can be influenced by several things like :
- Not suitable equipment.
- Incorrect calculation.
- Manipulation of the measuring results.
- MSA samples taken randomly with too little variations between them.
- ......etc.

Please search here and if you come up with more questions I am sure you are welcome here.

Best regards,

Antoine

Hello,

I am now going into MSA and I would like to know if the MSA is to be done on each measuring equipment or to each type of measuring equipment? I have been told that it is to be done on each type of equipment (one equipment of each type), but I don't think it is OK. I believe it should be performed on each measuring equipment. I have read the MSA manual 3rd edition, but this is not specified.

Thank you
Andreea

How do you manage/calculate (TAR) Tolerance Accuracy Ratio

How do you manage/calculate (TAR) Tolerance Accuracy Ratio for a one sided specification?
Example: Micrometer Accuracy is +/- .0002" The part specification is .035".

I believe that TAR is the Test Accuracy Ratio. See bottom of page one of this (broken link removed).

If you mean this in the context of MSA, the proper metric is either P/T Ratio or GRR as %Tol. You do not use the stated gage accuracy, but perform an MSA study. In the event of a one-sided tolerance, these metrics break down. You would be better off creating a gage performance curve or calculating the Probable Measurement Error (PME) as described by Donald Wheeler.

Rule of 10:1 has cleared from above posts for ndc the followin may be felpful to you.

Ndc is the no. of distinct Category, ndc concept comes into the picture from the 3rd addition of AIAG MSA manual before that the same would known as Gague classification Ratio.

It is calculated by dividing the standard deviation for parts by the standard deviation for gage, then multiplies by 1.41
Ndc = 1.41 (PV/GRR)

Now the most important thing what is the significance of the ndc,

This number represents the no. of non-overlapping confidence intervals that will span the range of product variation. You can also think of it as the number of groups within your process data that your measurement system can determine.

The AIAG suggest that when the no. of distinct category is less than 2, the measurement system is of no value for controlling the process, since one part cannot be distinguished from another.
When the ndc is 2, the data can be divided into two groups, say high or low.
When the ndc is 3, the data can be divided into 3 groups, say low, middle and high
A value of 5 or more denotes an acceptable measurement system.

Lets I will try to clear it with an example:
Let the range for your data varies from 0 to 0.20 and the value of ndc is 4, then the meaning of this is :
Your data is classified into 4 categories whose range varies as:

i) From 0 to 0.05
ii) From 0.05 to 0.10
iii) From 0.10 to 0.15
iv) From 0.15 to 0.20

AIAG states the "10:1 rule of thumb" on MSA 3rd edition page 43-44. They state that it can be considered a starting point, but that it "does not include any other element of the measurement system's variability." ndc (number of distinct categories) uses the gage study to generate statistically significant "buckets" or true gage resolution versus the indicated gage resolution or "readability" or "discrimination" (number of graduations, digits, etc. on the gage).

On page 117, they claim that the ndc should be greater than 5. And that may be true for general measurement. But it is woefully inadequate for SPC!

The most key statement is "If the measurement system lacks discrimination (sensitivity or effective resolution), it may not be an appropriate system to identify the process variation or quantify individual part characteristic values. All parts in the same category will have the same value for a measured characteristic."

On page 45 through 46, they indicate the need for good resolution in order to have SPC be effective. They claim 5 categories is sufficient for SPC, which, again, is woefully inadequate. You should have 5 categories on either side of the mean - if you are using X-bar-R charts or similar - to have enough resolution to utilize Western Electric rules (or similar). In fact, on page 46 they indicate "adequate resolution would be for the apparent resolution to be one tenth of the total process six sigma standard deviation." For SPC, I prefer the following:


ndc (for SPC) = ((UCL-LCL)*1.41)/(GRR) >10

This calculation assures 10 statistically significant categories within the control limits.

You really have to be careful with NDC.
An NDC of 5 is roughly equivalent to a %study variable of 30%, which is only marginally acceptable.
An NDC of 14 or 15 starts to give you a %study variable of 10% or lower, which is ideal.

Also the NDC like %study variable can only tell you how good your gage is at measuring the items used in that study. If your selection of parts does not represent the process then NDC can be a fairly meaningless number like %study in those cases.

I dont think NDC was meant to be used as a judgement of is my gage good or bad, it is there to add more understanding. It is equivalent to the %study variable, but is a rounded number.

I realise I am echoing some of what Bob says here, but you dont want to mistake 5 ndc for good and make mistakes because of it.

I agree you do have to be careful. But, it is absolutely worth considering to help clarify if a gage is anywhere near any value for its intended use. The calculation I listed above does extend the value of the concept to deal with the full range of the control limits, whereas the using PV in the original ndc calculation is limited to the samples in the study.

At a minimum, I find it a simple concept to move people away from the 10:1 readability (old school, back yard) to a resolution that considers gage system variability, as the ndc attempts to do. What you really want is statistically significant resolution - any way you can get there.