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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.

[p,h] = capaplot(data,specs) additionally returns handles to the plot elements in h.

capaplot treats NaN values in data as missing, and ignores them.


collapse all

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

Introduced before R2006a

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