Wanna talk sampling plans?
I personally am not a big fan of sampling plans, but that is another story.
How do you determine the OC curve in the first place?
The OC curve is developed by determining the probability of acceptance for several values of incoming quality. Pa is the probability that the number of nonconforming in the sample is equal to or less than the acceptance number for the sampling plan.
There are three distributions that can be used to find the probability of acceptance: the hypergeometic, binomial and the Poisson distribution. The Poisson distribution is the preferred because of the ease of Poisson table use. Be sure you can satisfy the assumptions for Poisson use. The Poisson formula is:
P = [(e^-np)*((np)^r)]/r!
n = Sample Size
p = Proportion nonconforming
r = Number of nonconforming or less
Assume n = 150 and r = 3, (called c in sampling plans) then:
Lot Percent Nonconforming
1%, np = (150)(0.01) = 1.50, P(r <= 3) = 0.93
2%, np = (150)(0.02) = 3.00, P(r <= 3) = 0.65
3%, np = (150)(0.03) = 4.50, P(r <= 3) = 0.34
4%, np = (150)(0.04) = 6.00, P(r <= 3) = 0.15
5%, np = (150)(0.05) = 7.50, P(r <= 3) = 0.06
6%, np = (150)(0.06) = 9.00, P(r <= 3) = 0.02
You then construct the table from these values with Lot Percent Nonconforming as the X value and Pa as the Y value.
Hope this helps.
Regards,
Don