Documentation |
Before going into production, many manufacturers run a capability study to determine if their process will run within specifications enough of the time. Capability indices produced by such a study are used to estimate expected percentages of defective parts.
Capability studies are conducted with the capability function. The following capability indices are produced:
mu — Sample mean
sigma — Sample standard deviation
P — Estimated probability of being within the lower (L) and upper (U) specification limits
Pl — Estimated probability of being below L
Pu — Estimated probability of being above U
Cp — (U-L)/(6*sigma)
Cpl — (mu-L)./(3.*sigma)
Cpu — (U-mu)./(3.*sigma)
Cpk — min(Cpl,Cpu)
As an example, simulate a sample from a 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