The World Statistics Day celebration continues here in the Community. We all need reliable data for sound decision making. Do you have a data source that you trust most? Head over to Discussions to tell us about it.
Choose Language Hide Translation Bar
Level III

How to script process capability analysis with best fit

I 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");
ColList = dt_spec<< get column names (numeric);
obj = dt_raw << manage spec limits (Y(eval(ColList)), load from limits table (dt_spec), save to column properties(1));
obj << close window;

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 ), );

Re: How to script process capability analysis with best fit

One 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.

Learn it once, use it forever!
Article Labels