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In 3D additive screen printing with constant snap-off, the inhomogeneous screen counterforce will influence the printing force and reduce the printing quality. The purpose of this paper is to study the relationship between scraper position, snap-off and screen counterforce and develop a variable snap-off curve for 3D additive screen printing to improve the printing quality.

An experiment was carried out; genetic algorithm (GA) optimization theoretical model, backpropagation neural network regression model and least square support vector machine regression model were established to study the relationship between scraper position, snap-off and screen counterforce. The absolute errors of counterforce of three models with the experiment results were less than 1.5 N, which was tolerated and the three models were considered valid. The comparison results showed that GA optimization theoretical model performed best.

The results suggest that GA optimization theoretical model performed best to represent the relationship, and it was used to develop a variable snap-off curve. With the variable snap-off curve in 3D additive screen printing, the inhomogeneous screen counterforce was weakened and the printing quality was improved.

In printing production, the variable snap-off curve in 3D additive screen printing helps improve the printing quality; this study is of prime importance to the 3D additive screen printing.