How to script process capability analysis with best fitI create script to generate the process capability. Below script works fine with the normal distribution (default). How can I assign the best fit to the calculation ?
dt_raw = data table ("raw_by_stage");<BR />ColList = dt_spec<< get column names (numeric);<BR />obj = dt_raw << manage spec limits (Y(eval(ColList)), load from limits table (dt_spec), save to column properties(1));<BR />obj << close window;<BR /><BR />obj = dt_raw << process capability(
process variables(eval(Collist) ),
Individual Detail Reports( 0 ),
Capability Box Plots( 0 ),
Overall Sigma Summary Report( 1 ),
Goal Plot( 0 ),
Capability Index Plot( 0 ),
);ScriptingRe: How to script process capability analysis with best fitOne of the fundamental tenets of process capability is that the process is known to be stable. A stable process is predictable. The distribution of the stable process should not change and should be determined from the new data each time capability is evaluated.
So I would recommend determining the distribution model at the beginning after it is demonstrated to be stable, and then use the same distribution model in the future. I would not use the 'best fit' approach every time at future evaluations.