qcc (version 1.3)

process.capability: 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, restore.par = TRUE)

Arguments

object

a `qcc' object of type "xbar"

spec.limits

a vector specifying the lower and upper specification limits.

target

a value specifying the target of the process. If missing the value from the `qcc' object is used if not NULL, otherwise the target is set at the middle value bewteen specification limits.

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 hist for more details.

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.

restore.par

a logical value indicating whether the previous par settings must be restored. If you need to add points, lines, etc. to a chart set this to FALSE.

Value

• Invisibly returns a list with components:
• nobs
  number of obserations
• 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 ($C_p$, $C_{pl}$, $C_{pu}$, $C_{pk}$, $C_{pm}$) and the corresponding confindence limits.
• 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.

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.

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. (2000) Introduction to Statistical Quality Control, 4th ed. New York: John Wiley & Sons. Wetherill, G.B. and Brown, D.W. (1991) Statistical Process Control. New York: Chapman & Hall.

See Also

process.capability.sixpack, qcc

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))