ss.cc: Control Charts

In emilopezcano/SixSigma: Six Sigma Tools for Quality Control and Improvement

Control Charts

Description

Plot control charts

Usage

ss.cc(type, data, cdata, CTQ = names(data)[1], groups, climits, nsigmas = 3)

Arguments

type	Type of chart (see details)
data	data.frame with the process data.
cdata	Vector with the controlled process data to compute limits.
CTQ	Name of the column in the data.frame containing the CTQ.
groups	Name of the column in the data.frame containing the groups.
climits	Limits of the controlled process. It should contain three ordered values: lower limit, center line and upper limit.
nsigmas	Number of sigmas to compute the limits from the center line (default is 3)

Details

If control limits are provided, cdata is dismissed and a message is shown. If there are no control limits nor controlled data, the limits are computed using data.
Supported types of control charts:

• mrMoving Range

Value

A plot with the control chart, and a list with the following elements:

LCL	Lower Control Limit
CL	Center Line
UCL	Upper Control Limit
phase	II when cdata or climits are provided. I otherwise.
out	Out of control points

Note

We have created this function since the qAnalyst package has been removed from CRAN, and it was used in the "Six Sigma with R" book to plot moving average control charts.

Author(s)

EL Cano

References

Cano, Emilio L., Moguerza, Javier M. and Redchuk, Andres. 2012. Six Sigma with R. Statistical Engineering for Process Improvement, Use R!, vol. 36. Springer, New York. https://link.springer.com/book/10.1007/978-1-4614-3652-2/.

See Also

ss.cc.constants

Examples

ss.cc("mr", ss.data.pb1, CTQ = "pb.humidity")
testout <- ss.data.pb1
testout[31,] <- list(31,17)
ss.cc("mr", testout, CTQ = "pb.humidity")

emilopezcano/SixSigma documentation built on April 19, 2023, 7:56 a.m.