Mathematics provides a virtually infinite library of shapes and patterns of incomparable beauty which, thanks to the automation of production processes, can be used in the production of design objects. In particular, reaction-diffusion patterns, which simulate the distribution of chemical substances, allow a large number of different patterns to be generated by varying the input parameters. These patterns can be used in the customization of objects, realized thanks to additive manufacturing (3D printers). This technique allows very complex shapes and unique pieces to be physicalized in a short space of time. This study has shown an accuracy degradation for virtual 3D models created with mathematical patterns in the discretization phase for printing platforms. A method to reduce the effect of discretization is proposed and preliminary results are shown to evaluate its effectiveness.

Increase the accuracy in direct 3D-Printing of mathematical Patterns for smart manufacturing

Bertacchini, Francesca;Bilotta, Eleonora;Demarco, Francesco;Pantano, Pietro;Scuro, Carmelo
2022-01-01

Abstract

Mathematics provides a virtually infinite library of shapes and patterns of incomparable beauty which, thanks to the automation of production processes, can be used in the production of design objects. In particular, reaction-diffusion patterns, which simulate the distribution of chemical substances, allow a large number of different patterns to be generated by varying the input parameters. These patterns can be used in the customization of objects, realized thanks to additive manufacturing (3D printers). This technique allows very complex shapes and unique pieces to be physicalized in a short space of time. This study has shown an accuracy degradation for virtual 3D models created with mathematical patterns in the discretization phase for printing platforms. A method to reduce the effect of discretization is proposed and preliminary results are shown to evaluate its effectiveness.
978-1-6654-1093-9
3D Printing; dimensional deviation; parametric modelling; pattern generation; smart manufacturing
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/341751
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