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 data, and plots the pdf of the resulting T distribution. The observations in data are assumed to be normally distributed. The output, 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 specs is shaded in the plot.
capaplot treats NaN values in data as missing, and ignores them.
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 = 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