Description Usage Arguments Value References See Also Examples
Provides an upper bound on the number of acceptable rejects or nonconformities in a process. This is similar to a 1sided upper tolerance bound for a hypergeometric random variable.
1  acc.samp(n, N, alpha = 0.05, P = 0.99, AQL = 0.01, RQL = 0.02)

n 
The sample size to be drawn from the inventory. 
N 
The total inventory (or lot) size. 
alpha 

P 
The proportion of items in the inventory which are to be accountable. 
AQL 
The acceptable quality level, which is the largest proportion of defects in a process considered
acceptable. Note that 
RQL 
The rejectable quality level, which is the largest proportion of defects in an independent lot
that one is willing to tolerate. Note that 
acc.samp
returns a matrix with the following quantities:
acceptance.limit 
The number of items in the sample which may be unaccountable, yet still be able to
attain the desired confidence level 
lot.size 
The total inventory (or lot) size 
confidence 
The confidence level 
P 
The proportion of accountable items specified by the user. 
AQL 
The acceptable quality level as specified by the user. If the sampling were to be repeated numerous times as a process, then
this quantity specifies the proportion of missing items considered acceptable from the process as a whole. Conditioning on the
calculated value for 
RQL 
The rejectable quality level as specified by the user. This is the proportion of individual items in a sample one is willing
to tolerate missing. Conditioning on the calculated value for 
sample.size 
The sample size drawn as specified by 
prod.risk 
The producer's risk at the specified 
cons.risk 
The consumer's risk at the specified 
Montgomery, D. C. (2005), Introduction to Statistical Quality Control, Fifth Edition, John Wiley & Sons, Inc.
1 2 3 4 5 6 7 
## A 90%/90% acceptance sampling plan for a sample of 450
## drawn from a lot size of 960.
acc.samp(n = 450, N = 960, alpha = 0.10, P = 0.90, AQL = 0.07,
RQL = 0.10)

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