How to calculate Subgroup Size for Machine Capability Study

G

gcpa81

#1
I have given the task of conducting machine capability study. We are going to run 50 parts through each machine. We are measuring all the significant characteristics in every single part (about 15 different measurement through CMM). My question is how does once calculate subgroup size?
Is is 1 or 50?
 
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bobdoering

Stop X-bar/R Madness!!
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#2
Should be one. There is no logical grouping for what you are doing. If you were doing 300, and checked 5, skipped 10, did 5 more, etc., then you would have subgroups of 5.
 

KCIPOH

Quite Involved in Discussions
#3
I have given the task of conducting machine capability study. We are going to run 50 parts through each machine. We are measuring all the significant characteristics in every single part (about 15 different measurement through CMM). My question is how does once calculate subgroup size?
Is is 1 or 50?
Should be one. There is no logical grouping for what you are doing. If you were doing 300, and checked 5, skipped 10, did 5 more, etc., then you would have subgroups of 5.
Hello bob,

I just want to clear out my doubt as i'm quite confuse with subgroup size definition in doing capability study, so, you mentioned should 1 and according to gcpa81, 50 parts and need to measure 15 significant characteristics, is that mean we take only 1 part out of 50 and measure the 15 characteristics? :confused:
 

bobdoering

Stop X-bar/R Madness!!
Trusted Information Resource
#4
Hello bob,

I just want to clear out my doubt as I'm quite confuse with subgroup size definition in doing capability study, so, you mentioned should 1 and according to gcpa81, 50 parts and need to measure 15 significant characteristics, is that mean we take only 1 part out of 50 and measure the 15 characteristics? :confused:
If he is doing a capability study where he runs 50 parts in a row through a machine, then measures the parts, then for any statistics used to analyze to data the subgroup should be 1. If you were to chart the parts and a traditional Shewhart chart was appropriate, then you would use I-MR. Some folks like to dream up a subgroup - maybe 4 or 5 - then use X bar -R or similar calculations. but, logical subgroups and made-up-to-make-software-work subgroups are two very different things. Only one is truly useful.

Of course, as an aside, no matter what process it is, you should do both a run chart and do curve fitting. Always get the data in time order sequence. If you find multi-modal variation, you will want to see if it is a time function. Dumping data into software and chugging out a "normal" curve, Cpks and Ppks is backyard stuff. The true distribution may not even support Cpks or Ppks. Also, it is critical that the measurement system not contribute to the distribution, or it may mask the true process distribution. Poor measurement technique and gage R&R can make a lot of non-normal distributions look normal by masking. So will overcontrol.

Interesting, huh? :popcorn:
 

Bev D

Heretical Statistician
Staff member
Super Moderator
#5
Just to throw another fast ball: 50 parts in a row will only show short term variation and could lead to a very misleading result. (lots of measuremetns with very littel useful information provided). The original intention of these 'capability studies' was that they would be comprised of subgroups* (samples) that were taken over time such that they would represent the full range of variation that the process could be expected to see when operating within the specified parameters. The subgroups are plotted in time series and the process is assessed for stability. The so-called 'short term capability' is then calculated from the within subgroup standard deviation and the 'long term capability' is calculated from the total standard deviation.

Short cuts are the quick way to confusion and wasted effort as evidenced by the large number of postings here asking "what went wrong with my Cpk study"?

*Of course, for very low volume production, the subgroup size would have to be 1 and the parts would be sequential.
 
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