In Sensitivity mode, ZEMAX takes the tolerances and predicts the degradation of performance. In Inverse Sensitivity mode, ZEMAX is given a target degradation of the merit function, and must find the tolerances that achieve it. Set up the tolerancer like so:

In the Set-Up tab



In the Criterion tab note that the 'Limit' box is now available. Press the CHECK button to get the nominal system tolerancing criterion:



and enter a target value of say 0.0075



so that each tolerance can degrade the tolerancing criterion to no more than l/130. Leave all other settings fixed and re-run the tolerancer.

The root-sum-square results show greatly improved performance:



And this is also seen in the Monte-Carlo results



However, 20 Monte-Carlo files is not enough. Roughly speaking, if there are n tolerances, you need at least n² Monte-Carlo files to sample the probability distributions adequately. As we have 24 tolerances, we need at least 24² = 576 Monte-Carlo files. I chose to perform 1000 Monte-Carlo samples, and obtained this result:




A review of the tolerances indicates that none are unreasonably tight as a result of the inverse tolerancing.