process.capability {qcc} | R Documentation |
Process capability analysis
Description
Computes process capability indices for a 'qcc' object of type "xbar"
and plot the histogram.
Usage
process.capability(object,spec.limits, target, std.dev, nsigmas,
confidence.level = 0.95, breaks = "scott",
add.stats = TRUE, print = TRUE,
digits = getOption("digits"), restore.par = TRUE)
Arguments
object |
a 'qcc' object of type |
spec.limits |
a two-values vector specifying the lower and upper specification limits. For one-sided specification limits, the value of the missing limit must be set to |
target |
a value specifying the target of the process. If missing the value from the 'qcc' object is used if not |
std.dev |
a value specifying the within-group standard deviation. If not provided is taken from the 'qcc' object. |
nsigmas |
a numeric value specifying the number of sigmas to use. If not provided is taken from the 'qcc' object. |
confidence.level |
a numeric value between 0 and 1 specifying the level to use for computing confidence intervals. |
breaks |
a value or string used to draw the histogram. See the help for |
add.stats |
a logical value indicating whether statistics and capability indices should be added at the bottom of the chart. |
print |
a logical value indicating whether statistics and capability indices should be printed. |
digits |
the number of significant digits to use. |
restore.par |
a logical value indicating whether the previous |
Details
This function calculates confidence limits for C_p
using the method described by Chou et al. (1990).
Approximate confidence limits for C_{pl}
, C_{pu}
and C_{pk}
are computed using the method in Bissell (1990).
Confidence limits for C_{pm}
are based on the method of Boyles (1991); this method is approximate and it assumes that the target is midway between the specification limits.
Value
Invisibly returns a list with components:
nobs |
number of observations |
center |
center |
std.dev |
standard deviation |
target |
target |
spec.limits |
a vector of values giving the lower specification limit (LSL) and the upper specification limit (USL) |
indices |
a matrix of capability indices ( |
exp |
a vector of values giving the expected fraction, based on a normal approximation, of the observations less than LSL and greater than USL. |
obs |
a vector of values giving the fraction of observations less than LSL and greater than USL. |
Author(s)
Luca Scrucca
References
Bissell, A.F. (1990) How reliable is your capability index?, Applied Statistics, 39, 331-340.
Boyles, R.A. (1991) The Taguchi capability index, Journal of Quality Technology, 23, 107-126.
Chou, Y., Owen D.B. and Borrego S.A. (1990) Lower Confidence Limits on Process Capability Indices, Journal of Quality Technology, 22, 223-229.
Montgomery, D.C. (2005) Introduction to Statistical Quality Control, 5th ed. New York: John Wiley & Sons.
Wetherill, G.B. and Brown, D.W. (1991) Statistical Process Control. New York: Chapman & Hall.
See Also
Examples
data(pistonrings)
attach(pistonrings)
diameter <- qcc.groups(diameter, sample)
q <- qcc(diameter[1:25,], type="xbar", nsigmas=3, plot=FALSE)
process.capability(q, spec.limits=c(73.95,74.05))
process.capability(q, spec.limits=c(73.95,74.05), target=74.02)
process.capability(q, spec.limits=c(73.99,74.01))
process.capability(q, spec.limits = c(73.99, 74.1))