Process capability plot
p = capaplot(data,specs)
[p,h] = capaplot(data,specs)
p = capaplot(data,specs) estimates
the mean of and variance for the observations in input vector
and plots the pdf of the resulting T distribution. The observations
data are assumed to be normally distributed.
p, is the probability that a new observation
from the estimated distribution will fall within the range specified
by the two-element vector
specs. The portion of
the distribution between the lower and upper bounds specified in
shaded in the plot.
[p,h] = capaplot(data,specs) additionally
returns handles to the plot elements in
data as missing, and ignores them.
Create a Process Capability Plot
Randomly generate sample data from a normal process with a mean of 3 and a standard deviation of 0.005.
rng default; % For reproducibility data = normrnd(3,0.005,100,1);
Compute capability indices if the process has an upper specification limit of 3.01 and a lower specification limit of 2.99.
S = capability(data,[2.99 3.01])
S = struct with fields: mu: 3.0006 sigma: 0.0058 P: 0.9129 Pl: 0.0339 Pu: 0.0532 Cp: 0.5735 Cpl: 0.6088 Cpu: 0.5382 Cpk: 0.5382
Visualize the specification and process widths.
capaplot(data,[2.99 3.01]); grid on