Duoadd§: a software to detect and export damages of 3d scanned objects
Visualitza/Obre
Estadístiques de LA Referencia / Recolecta
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/334898
Tipus de documentText en actes de congrés
Data publicació2019
EditorCIMNE
Condicions d'accésAccés obert
Tots els drets reservats. Aquesta obra està protegida pels drets de propietat intel·lectual i
industrial corresponents. Sense perjudici de les exempcions legals existents, queda prohibida la seva
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Abstract
The recent appearance of hybrid CNC machines – which can both add and remove material to an object
– has facilitated a new type of approach to the problem of repairing damaged com- ponents. Up to
now, repair operations have been carried out manually and for this reason they are errors prone,
costly and time consuming. The use of precise and repeatable CNC machines in this field is
therefore very attractive for the sake of reliability and repeatability. One of the biggest
obstacles on the automation of the repairing process is that the CAM software requires a solid CAD
model to create the toolpaths needed to perform additive operations. The present work proposes the
use of octrees to detect the damaged spot starting from the 3D scan of the damaged object. A
software named DUOADD has been developed to convert these informa- tions into a CAD model suitable
to be used by the CAM software. The new workflow designed to perform a complete repair operation is
here described. DUOADD allows to approach the repairing problem from a new point of view opening
the doors to save both time and money. The successful application of the entire process to repair a
damaged die injection mold is also here reported.
§DUOADD=DUOADD Uses Octree sAs Damage Detector
CitacióPerini, M.; Bosetti, P. Duoadd§: a software to detect and export damages of 3d scanned objects. A: Sim-AM 2019. "Sim-AM 2019 : II International Conference on Simulation for Additive Manufacturing". CIMNE, 2019, p. 391-402. ISBN 978-84-949194-8-0.
ISBN978-84-949194-8-0
Fitxers | Descripció | Mida | Format | Visualitza |
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Sm_AM-2019_37-DUOADD§ A SOFTWARE TO DETECT.pdf | 1,088Mb | Visualitza/Obre |