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Direct broad band monitoring of coating production is among the most promising modern monitoring approaches that attracts wide attention of researchers and production engineers. As all other monitoring techniques it has some advantages and disadvantages. The main disadvantage of direct broad band monitoring is the effect of accumulation of thickness errors with the growth of a number of deposited layers while the main advantage of this technique is believed to be the effect of errors self-compensation. Both effects are connected with the correlation of thickness errors that takes place because errors in previously deposited layers influence monitoring spectra for the currently deposited layer. Correlated thickness errors have nevertheless also a random nature because there are many random factors influencing the deposition process and the applied monitoring procedure. It is not possible to describe such errors statistically and the only one way to investigate possible results of thickness errors correlation is to perform wide sets of computational manufacturing experiments in which all major error factors of the deposition process and monitoring procedure are simulated. In the presented work we apply computational manufacturing experiments to the investigation of the effect of errors self-compensation associated with direct broad band monitoring. We demonstrate that for some types of optical coatings this effect may be very strong. The main outcome of the presented approach is a possibility to predict for what types of optical coatings direct broad band monitoring is expected to provide better production yield as compared to other monitoring techniques.