This topic contains 14 replies, has 8 voices, and was last updated by nizar 4 months ago.
I want to calculate sample size/frequency for online checking during shift/day. As previous data/study is not available, so i take samples & calculaate present status. With ref to study below are the outcomes:
– Process Capability (Cpk) = 1.18
– Sample Mean = 0.46044
– Std Dev = 0.01195
– Variance = 0.00014
– Product Specification = 0.40 (+0.02 / +0.12) mm OR 0.42 to 0.52 mm
– Confidence Interval = 95%
– Production Qty/Shift = 16000
What should be sample size set for checking per shift?
Never been in manufacturing.. but will look at this post for more knowledge.. I came across a nice link in Wikipedia.. may be will help!
@abhishek5380 – please do your own homework/test problems yourself. If you’d like to suggest an answer and back it up with how you derived that answer, you might get some feedback on whether you approached it correctly or not.
@MBBinWI Answer is 212. Please have original poster verify my answer ;-).
@Darth – all numerical answers resolve to 42 (see Hitchhikers guide to the galaxy for corroboration). Besides, depends on what you choose for power value.
@abhishek5380 – how can you have a spec with a nominal value of 0.40 and a tolerance of +0.02 to +0.12? (as you indicate this makes the tolerance range from 0.42 to 0.52 which doesn’t include 0.40). I’ve never seen such a tolerance spec.
MBBinWI, What do you mean you’ve never seen such a tolerance spec? You need to read more about your nearest neighbor state – Minnesota. That spec was developed in Lake Wobegon in response to the State of Minnesota’s query concerning the children in that town.
@rbutler – delusions of a socialist, I don’t put much credence in such tales. (besides, I have more than a casual appreciation for the lovely land of 10,000 lakes).
@MBBinWI So, is the count of lakes discrete or continuous? I “how many lakes” is discrete while area, depth, temperature would be continuous. What say you?
Abusing the topology of Rn , we can conclude that this discussion
is akin to a Mobius Strip.
@abhishek5380 Buy the students version of Minitab and when you get stuck call tech support and you won’t have to take all this abuse.
Thanks for explaining the flattening process, nominal is not nominal, but rather the starting diameter roughly) which gets flattened to slightly larger diameter, so so you simply want to trend the data and set up SPC charts using a sampling plan based on your preliminary study data, right? I think if you had explained that in first post, DARTH would have been less offensive..or wrong. But Mike Carnell is right, in that stat software on sampling is abundant, and even free on web.
However, the cost of sampling and cost of NOT sampling should be added to the discussion, and economics rather than statistics often determines the optimal sampling plan, in my experience. If the gaging is automated, simply capture the readings and plot the data. If its manual data entry, typos by operators can be 2% of alarms, or operators can “flinch” giving no alarms, but a strange clustering of data just inside of the spec limits. So using real process control limits, rather than spec limits, to alert machine keeps of drift or shift or high variability is useful. But if the only question is a homework assignment asking for best sampling plan…sorry…but there is no economic answer possible, and statistics can be very misleading…in my experience.
@mclayton200 NICE JOB!!! You are posting to a thread from March 2012. Way to stay on top of things.
@Darth: Sorry if my tardiness offends you.
I only view this site a few times a year, since manufacturing discussions seem to be few, and since they are kept online for long times, they can be useful to those with similar problems…IF the responses stay one the subject. So since this one went way off topic in typical social-media-type rants, I thought I would try to conclude it with some perspective on the process of flattening, and its very confusing engineering measurement limits, a common problem in manufacturing that require careful (with diagrams) definitions. At least @MBBinWI was as confused as I was until the comments about the process were clearer.
Thanks for keeping these few manufacturing discussions online. I also go back through the archives for learning examples. Sampling plan questions are always problematic, as economic costs of sampling FREQUENCY as well as sample size per SPC subgroup are more important than the textbook rules suggest.
Can I use a margin of error 0.03 with confidence level of 95% when calculating sample size?? or is it a must to use a margin of error with its complentary confodence level meaning 0.1 woth 90% condidence level 0.05 with 95% confidence leve 0.03 with 97% and 0.01 margin with 99% confidence level??.
OR can i use any margin of error with any confidence level when calculating sample size???