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.
Simulate a sample from a process with a mean of 3 and a standard deviation of 0.005:
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: 0.0047 P: 0.9669 Pl: 0.0116 Pu: 0.0215 Cp: 0.7156 Cpl: 0.7567 Cpu: 0.6744 Cpk: 0.6744
Visualize the specification and process widths:
capaplot(data,[2.99 3.01]); grid on