The implementation of UV-technologies has revealed problems associated with the migration of harmful components of the ink layer to the back of the packaging in contact with the packaged products. The reason for this migration is the incomplete reaction of the UV-ink components due to a decrease in the intensity of UV-radiation, the mismatch between the absorption spectrum of the photoinitiator and the spectrum of the UV-source and the inhibitory effect of oxygen. It has been established that the decay products of photoinitiators, which occupy the third position in terms of concentration content in the ink composition, have a potential ability to migrate. To prevent such migration, polymerized photoinitiators have been developed that differ from conventional ones by higher molecular weight. Accordingly, a study of the effect of the photopolymerization degree of UV-ink on the presence of residual odor, as a direct characteristic of the ability of ink components to migrate has been done. It has been found that at the photopolymerization degree of 84%, the average value of the residual odor level is 4 points, and at the photopolymerization degree of 96%, it is 2.8 points. Using the obtained data on the presence of residual odor and the data on the influence of molecular weight of photoinitiators, a knowledge base has been formed with the condition "if-then", a logical scheme has been formed and fuzzy logical equations of influence of established factors on the migration capacity of UV-ink have been constructed. The establishment of a universal set and evaluation terms has made it possible to form a quantitative indicator of migration of UV-ink components. The formed fuzzy knowledge base has been checked when modeling with the help of the Fuzzy Logic Toolbox system of the Matlab technological calculation environment according to Mamdani principle, using the method "Center of gravity" for the dephasification operation. The suggested method of calculating the migration capacity of UV-inks has made it possible to construct a two-factor forecasting model.
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