Control Chart CpK dilemma - Defect Per Unit data on a single production line

S

SHARON MYNHARDT

#11
Hi guys

I am new to Elsmar and Quality. My name is Sharon. I need help with the following.

How do you interpret when a process is in or out of control.

CPK 1.33
CPK 1.53
CPK 1.00

Which is in control, which is stable and which is out of control.

Please help.

Thanks

Sharon
 
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D

Darius

#12
First...Wellcome to the cove.

The cpk does not explain that issue.

The Cpk just evaluate the variation against the specs and make a penalty for not being the center to them.

The Cpk it self doesn't tell how many samples where taken, the sample size could make the cpk estimate :mg: have large or small confidence interval. As I said in other post is better to use Cpk minimum estimated value so you can compare the Cpk form different sample sizes correctly (or establish a minimum of 100 samples for example)

How can be answered "is the process stable?", is not clear, there are two (at least) phylosofies.
1- Not presenting any pattern on the control chart (well maybe 2 in a 100 sample could be considered stable). The issue here is wich patten apply to your process, not every GE rule applies to any process.
2- I found scarse information about this other one but IMHO the right way. take SPC as statistical hypotesis testing (to compare mean and variation with a "t" and an "F" test) from one period of time to the other (use 90% confidence tables because is not a controlled experiment). The root on this is that if you have the same mean and the same variation, the process could be predicted.

Try to read this... (is not publicity but thanks to Donald Wheeler's SPC Press and their reading room), it's a MUST.
A change in terminology:applause:
 
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D

Darius

#14
There is not much to say from the file
Cpk 1.47, that according to my calculus is not less than 1.2, nice Cpk
The sample size looks to me a little bit low and the data looks not gaussian (more data on the lower 32 without any data bellow). On the data looks something like a periodic ups and downs but from the sample size is hard to say.

It's not 6Sigma but loks fine

And you can say it's in control, no outliers and no visible patterns from the data (but looks a little bit non natural, maybe can the periodic ups and downs be analized and increase the capability of your system).
 
J

janedoe

#15
Hey Scott,
Your situation calls for the use of a C-chart. It measures defects / unit which, in this case, is defects per machine. The particular size of the machine matters little.

Your selection of the proper chart for attribute studies is based on what is know as the Poisson distribution, and it applies to the C and U chart where binomial data reflects the P and NP chart usage.

How to tell when a Poisson based (C or U) chart are needed?
Here's what you do to answer this question. Look at your process and ask yourself: 'If I can track defects...is it also possible for me to track non-defects'? Clearly, you can not track non-defects...such as paint defects or scratches. That is, what would a non-paint defect look like?

See what I mean? You can't track the non-defect or it simply does not have any real meaning.

The correct method would be to use a C-chart since the lot size has been established as a single unit. A U-chart, too, could be used but the C-chart will provide more meaningful information such as "there are 1.4 defects per unit".

Hope that helped.
 

Miner

Forum Moderator
Staff member
Admin
#16
Please have a look at my attachment

Thanks
Sharon,

Take a look at the attached histogram of your data. It is non-normal, though does appear stable. You cannot calculate a standard Cpk with this type of data.

Before making any recommendations such as attempting to transform the data, can you explain the process that created these diameters?

This is reminiscent of a screw machine where the diameters are turned down to a hard stop. You can have diameters greater than the stop, but none less than the stop.
 

Attachments

F

flyin01

#17
4) Determine root cause(s),
5) implement corrective action(s) (Make it/them go away),
6) continue to monitor to determine if it in fact it/they did go away.


I agree with you. These can not be stressed enough, reliable rca is crucial, the problem is that everyone always has a action plan, but how realistic are they and nr 6 is often forgotten. It is easy to forget to verify that the problem was solved before moving on to other problems.
 
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