To set spec limits at +/-15% from the mean, use the following script as an example. This will allow you to easily check for and report any points beyond 15%.
// Based on txnelson's post from Nov 9, 2023.
// The usual frontmatter:
Open( "$SAMPLE_DATA/Quality Control/Diameter.jmp" );
Names Default To Here( 1 );
dt = Current Data Table();
// Change column property: DIAMETER
theMean = Col Mean(:DIAMETER);
Eval(
Substitute(
Expr(
dt:DIAMETER << set property(
"Spec Limits",
{LSL( _LSL_ ),
//Target( _Target_ ),
USL( _USL_ ),
Show Limits( 1 )}
)
),
Expr( _LSL_ ), 0.85*theMean,
//Expr( _Target_ ), theMean,
Expr( _USL_ ), 1.15*theMean
)
);
To simultaneously check for both points beyond 7.5% and points beyond 15%, that's a bit trickier. One way would be to set 7.5% as the known "historical sigma" of the process. Then you could use the built in Warnings functions in Control Chart Builder to check for points beyond 1 and 2 sigma, respectively.
Set 7.5% of the mean as the "historical" Sigma using the Red Triangle -> Set Sigma option. Then, you could right click the graph and use Warnings -> Customize Tests and change Test 1 to check for points beyond 1 sigma (or script these steps as shown below).
Then, set KSigma to 2, and now Test Beyond Limits will also check for points beyond 15%.
This isn't usually how control charts are used, but it would get the job done.
To do so, append this to the script above:
// Control chart builder with manually set historical sigma
Eval(
Substitute(
Expr(
Control Chart Builder(
Variables( Y( :DIAMETER ) ),
Set Sigma( _sigma_ ),
K Sigma( 2 ),
Customize Tests( Test 1( 1, "1" ) ),
Chart( Position( 1 ), Limits( Spec Limits( 1 ) ) )
);
),
Expr( _sigma_ ), 0.075*theMean,
)
);