Digital innovation of the last few decades has meant that the Internet of Things paradigm (IoT) is increasingly applied to new sectors of the industry, such as rapid prototyping and 3D printers. This has allowed the digitization of production processes and the customisation of products through the Internet by users and consumers. A first analysis has highlighted that the last generation 3D printers have a resolution higher than the final achieved accuracy evaluated by comparing the CAD model and the printed object. The goal is to study the whole process, detect the operations that degrade the accuracy and reduce their influence. This study has highlighted that the accuracy degradation is in the discretization of the CAD model that is required by the printing platforms. In this paper, an innovative method reducing the effect of the discretization is proposed and preliminary results are shown to assess its effectiveness.

Preliminary study of an innovative method to increase the accuracy in direct 3D-Printing of NURBS objects

Bertacchini F.;Bilotta E.;Carni D. L.;Demarco F.;Pantano P.;Scuro C.
;
Lamonaca F.
2021-01-01

Abstract

Digital innovation of the last few decades has meant that the Internet of Things paradigm (IoT) is increasingly applied to new sectors of the industry, such as rapid prototyping and 3D printers. This has allowed the digitization of production processes and the customisation of products through the Internet by users and consumers. A first analysis has highlighted that the last generation 3D printers have a resolution higher than the final achieved accuracy evaluated by comparing the CAD model and the printed object. The goal is to study the whole process, detect the operations that degrade the accuracy and reduce their influence. This study has highlighted that the accuracy degradation is in the discretization of the CAD model that is required by the printing platforms. In this paper, an innovative method reducing the effect of the discretization is proposed and preliminary results are shown to assess its effectiveness.
978-1-6654-1980-2
3D-Printer
Accuracy
Dimensional deviation
Industry Internet of Things
Measurement uncertainty
Tolerances
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/323675
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