qcs.hat.cpm {qcr} | R Documentation |
Process capability index (estimate cpm)
Description
Estimate "cpm"
using the method described by Kerstin Vannman(2001).
Usage
qcs.hat.cpm(
object,
limits = c(lsl = -3, usl = 3),
target = NULL,
mu = 0,
std.dev = 1,
nsigmas = 3,
k0 = 1,
alpha = 0.05,
n = 50,
contour = TRUE,
ylim = NULL,
...
)
Arguments
object |
qcs object of type |
limits |
A vector specifying the lower and upper specification limits. |
target |
A value specifying the target of the process.
If is |
mu |
A value specifying the mean of data. |
std.dev |
A value specifying the within-group standard deviation. |
nsigmas |
A numeric value specifying the number of sigmas to use. |
k0 |
A numeric value. If the capacity index exceeds the |
alpha |
The significance level (0.05 for default) |
n |
Size of the sample. |
contour |
Logical value indicating whether contour graph should be plotted. |
ylim |
The y limits of the plot. |
... |
Arguments to be passed to or from methods. |
References
Montgomery, D.C. (1991) Introduction to Statistical Quality Control, 2nd
ed, New York, John Wiley & Sons.
Vannman, K. (2001). A Graphical Method to Control Process Capability. Frontiers in Statistical Quality Control,
No 6, Editors: H-J Lenz and P-TH Wilrich. Physica-Verlag, Heidelberg, 290-311.
Hubele and Vannman (2004). The E???ect of Pooled and Un-pooled Variance Estimators on Cpm When Using Subsamples.
Journal Quality Technology, 36, 207-222.
Examples
library(qcr)
data(pistonrings)
xbar <- qcs.xbar(pistonrings[1:125,],plot = TRUE)
mu <-xbar$center
std.dev <-xbar$std.dev
LSL=73.99; USL=74.01
qcs.hat.cpm(limits = c(LSL,USL),
mu = mu,std.dev = std.dev,ylim=c(0,1))
qcs.hat.cpm(object = xbar, limits = c(LSL,USL),ylim=c(0,1))