EWMA_p_chart_two {EATME}

A two-sided EWMA-p control chart

Description

This function displays two-sided EWMA-p chart control charts based on in-control and out-of-control data that are number of defectives. In the presence of measurement error, this function is able to provide suitable charts with corrections of measurement error effects.

Usage

EWMA_p_chart_two(
  ICdata,
  OCdata,
  lambda,
  n,
  pi1 = 1,
  pi2 = pi1,
  ARL0 = 200,
  M = 500,
  error = 10
)

Arguments

ICdata

The in-control data for attributes.

OCdata

The out-of-control data for attributes.

lambda

An EWMA smooth constant, which is a scalar in [0,1].

n

A sample size in the data.

pi1

The proportion that the observed defectives are the same as unobserved ones.

pi2

The proportion that the observed non-defectives are the same as unobserved ones.

ARL0

A prespecified average run length (ARL) of a control chart in the in-control process.

M

The number of simulation times for the Monte Carlo method

error

The tolerant for the absolute difference between an iterated ARL value and prespecified ARL0.

Value

The first chart is an EWMA-p chart obtained by the in-control data, and the second chart is an EWMA-p chart based in the out-of-control data. In two figures, horizontal solid lines represents upper control limit (UCL) and lower control limit (LCL), black solid dots are detections of in-control data, and red solid dots are detections of out-of-control data.

References

Chen, L.-P. & Yang, S.-F. (2022). A new p-chart with measurement error correction. arXiv: 2203.03384.

Examples

library(qcr)
data = orangejuice
IC = data[31:54,1]
OC = data[1:30,1]
set.seed(2)
EWMA_p_chart_two(IC,OC,0.05,50,1,1,200,100,20)