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Create Error Function vs. Cycle Chart

Knowing the contribution of each component of the error function can help you to pick appropriate component weights to start an optimization. For example, you can set a weight on the constraint component so that it has a contribution similar to the aberration component to ensure that the optimizer pays equal attention to both components at the start of the optimization. With the tolerance sensitivity error function SAB, you may wish to try optimizing with different starting ratios between the two.

You can check the starting contribution from each component by running an evaluation-only optimization cycle with the maximum number of cycles set to 0 (MXC 0). You can check the contribution from each component, and adjust optimization weights using this information.

For example, the command  

AUT;MXC 0;SAB FA 1;EFL = (efl);DIY FL = 0; WTC 1;GO

can generate output with this error function content:

CYCLE NUMBER 0:

ABERR F. =     1407.08283001
SAB F.   =      588.84811418
CONST F. =      173.50310670
ERR. F.  =     2169.43405088

In order to efficiently determine the best ratios between components, you could use a macro that tries several different ratios. You can use the database item (AUT.ERF) to report the total error function after the optimization, but to get to the different components, you’ll need to capture the optimization output into a Worksheet Buffer and extract the right data from it. Macro syntax to accomplish this task could look like:

BUF Y !Record output into worksheet buffer B0

!Run an evaluation only optimization cycle
AUT;MXC 0;SAB FA 1;EFL = (efl);DIY FL = 0; WTC 1;GO

BUF N !Stop recording into worksheet buffer B0

!Search B0 for string "SAB F." and store it in variable ^AUTSAB
BUF FND B0 "SAB F." 
^AUTSAB == (BUF.NUM B0 IC JL)

WRI ^AUTSAB
!This reports ^AUTSAB = 588.848

You can then use the ratio ^AUTSAB/(AUT.ERF) to determine a suitable tolerance sensitivity (SAB) weight. Note that doubling a weight factor will multiply the error function contribution by the square of the weight. For example, changing the SAB weight to 2 in the example above will cause the tolerance sensitivity contribution to jump to 2355, or 4 times the contribution when the weight was 1.

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