LTPDvar (version 1.2.1)

planAOQL: Calculation of AOQL plan for sampling inspection by variables

Description

Calculation of AOQL plan (sample size \(n\) and critical value \(k\)) for sampling inspection by variables. Plans minimize mean inspection cost per lot of process average quality and at the same time satisfy limit on average outgoing quality (see AOQ).

Usage

planAOQL(N, pbar, pL, method = c("exact", "napprox","ewmaSK","ewma2"), cm = 1,
	intdif = 20,lam=1)

Arguments

N

lot size (number of items in the lot)

pbar

process average fraction defective

pL

average outgoing quality limit

method

type of OC (operating characteristic) used, either "exact" (default) using non-central t-distribution, or "napprox" for approximate OC; if EWMA statistic is to be used, "ewmaSK" stands for the sigma known case, "ewma2" stands for the sigma unknown case

cm

parameter used in cost function of plans (see Ims) and defined as cost of inspection of one item by variables divided by cost of inspection of the item by attributes, default value 1

intdif

parameter used in finding \(n\) when method other than "napprox", controlling the width of interval to be searched in for sampling plan optimal w.r.t. cost, difference from interval centre (\(n\) resulting from planLTPD(..., method = "napprox") to lower or upper bound, default value 20

lam

smoothing parameter in case that EWMA statistic is used

Value

ACSPlan-class object

References

Klufa J (1997) Dodge-Romig AOQL single sampling plans for inspection by variables. Statistical Papers 38: 111 - 119

See Also

LTPDvar-package, OC, AOQ, ACSPlan-class, Ims

Examples

# NOT RUN {
# find AOQL plan
planAOQL(N=1000,pbar=0.005,pL=0.01, method="napprox", cm=1.5);
planAOQL(N=8000, pbar=0.003, pL=0.01, cm=1.5,method="ewmaSK", lam=0.9,intdif=40);
planAOQL(N=8000, pbar=0.003, pL=0.01, cm=1.5,method="ewma2", lam=0.9);
# }