Process Capability Analysis Binomial or Normal using Minitab 15

B

brahmaiah

#31
Interesting thread surrounding process capability and Binomial data. Would you not want to transform the data as it is a unilateral spec and non-normal?

From this transformed data, the new control limits could be established and pre & post modification results for capability and p or u control chart derived.

However this was just a thought, if I am flawed in my thought process - please let me know. I come across this issues sometimes too!

Thanks.
Eric
Your thoughts are too wild and have no theoritical or practical basis.
V.J.Brahmaiah
 
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B

brahmaiah

#33
What would you suggest? Can you help?
SPC has been discussed in this forum almost inexhaustively I suggest you to refer previous posts on this subject. If you still want me to help, please provide following information on the process data you are refering to;
1.Operation name
2.Machine name
3.Method of data collection
4.The collected data in an appropriate chart
5.Is the machine automatic/CNC/Manual
6.Characeristics measured and the tolerance
All are important to calculate the process capability
V.J.Brahmaiah
 

Stijloor

Staff member
Super Moderator
#34
SPC has been discussed in this forum almost inexhaustively I suggest you to refer previous posts on this subject. If you still want me to help, please provide following information on the process data you are refering to;
1.Operation name
2.Machine name
3.Method of data collection
4.The collected data in an appropriate chart
5.Is the machine automatic/CNC/Manual
6.Characeristics measured and the tolerance
All are important to calculate the process capability
V.J.Brahmaiah
Is that your suggestion for this post?

Stijloor.
 

tahirawan11

Involved In Discussions
#36
Hi,

1.Operation name
Curing of composite material

2.Machine name
The product is a 'Carbon Fibre Reinforced Slab' made by a similar process

3.Method of data collection
Finished part is scanned using a NDT ultrasound scanner and a 'image' is obtain which gives us the 'void content'. For detail see previous posts.

4.The collected data in an appropriate chart
attached

5.Is the machine automatic/CNC/Manual
the process is a mix of automatic and manual work

6.Characteristics measured and the tolerance
'Voids content' or Porosity left within product, it is given in 'percentage' and the tolerance limit is 0-15. The values cannot go below 0. The lower the values the better it is.

We have only one case where the end product was out of specs (voids % 16) and based on root cause analysis done so far we have seen a good co-relation relation between 'vacuum lost' and 'void %'. During the manufacturing process we apply vacuum to the product to take out the air and if we have a 'vacuum lost' during the process we can see high void content. I have also seen that either we can have very good parts (no vacuum lost) or very bad parts (vacuum lost) and very few parts between lower and upper specs. limits. So i was thinking control chart may not be very useful to predict any future performance. After the process change i have seen improvements but now i am more interested to know how the process will behave in future.
 

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bobdoering

Stop X-bar/R Madness!!
Trusted Information Resource
#37
One of the things we have not discussed is the variation from the measurement process. Have you performed a gage R&R to see how much of the variation - or even the fliers - come from the measurement itself? Both the measurement and the process are very "organic", so it would be good to sort out each one's participation.

A key to any statistical evaluation is total variation. Your data represents all variation - not just the variation of the process. It is always a good reminder to consider that when we look at data.

:topic: Your process reminds me of the old days when I molded carbon fiber/polyimide composite aircraft engine bearings and components. Ah, those were the days.... Do you look at cracking (in addition to porosity) as a participant in the voids, too?
 
B

brahmaiah

#38
Hi,

1.Operation name
Curing of composite material

2.Machine name
The product is a 'Carbon Fibre Reinforced Slab' made by a similar process

3.Method of data collection
Finished part is scanned using a NDT ultrasound scanner and a 'image' is obtain which gives us the 'void content'. For detail see previous posts.

4.The collected data in an appropriate chart
attached

5.Is the machine automatic/CNC/Manual
the process is a mix of automatic and manual work

6.Characteristics measured and the tolerance
'Voids content' or Porosity left within product, it is given in 'percentage' and the tolerance limit is 0-15. The values cannot go below 0. The lower the values the better it is.

We have only one case where the end product was out of specs (voids % 16) and based on root cause analysis done so far we have seen a good co-relation relation between 'vacuum lost' and 'void %'. During the manufacturing process we apply vacuum to the product to take out the air and if we have a 'vacuum lost' during the process we can see high void content. I have also seen that either we can have very good parts (no vacuum lost) or very bad parts (vacuum lost) and very few parts between lower and upper specs. limits. So i was thinking control chart may not be very useful to predict any future performance. After the process change i have seen improvements but now i am more interested to know how the process will behave in future.
Thank you for your detailed information about your curing process.
'The data' ie the actual porosity observed falls under non-normal distribution.The characteristic(porosity)has a one sided specification means there is no value below zero.Process capability calculation in the normal procedure is not possible.You have to decide with your customer another method to asses the process capability of your process.This is the recommendation of Clause no.2.2.11.5 of PPAP -fourth edition.
Even if you are not following TS16949 requirement.The theory is same.
Now there are two alternative methods for you to proceed (in agreement with your customer).They are:
1.100% inspection for porosity.
2.Sampling inspection with '0' AQL.and
100% control on the optimum vacuum level in your moulding process.
Your control plan should specify minimum required vacuume level in the process characteristic colomn.
In addition ,your ultrosonic flaw detection process could contain a huge MEASUREMENT UNCERTAINITY FACTOR ang GRR VARIATION.
V.J.Brahmaiah
 

Statistical Steven

Statistician
Staff member
Super Moderator
#39
What is wrong with using the capability analysis for a nonnormal distribution that is available in Minitab? It also has capability for binomial and Poisson.
 

bobdoering

Stop X-bar/R Madness!!
Trusted Information Resource
#40
What is wrong with using the capability analysis for a nonnormal distribution that is available in Minitab? It also has capability for binomial and Poisson.
That is a good question - since this is a Minitab forum. My guess Weibull distribution is more appropriate, however, for the unilateral void issue.
 
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