Point Cloud Data for Silicone Liquid Deposition Modeling

DOI

This dataset contains a set of point clouds acquired on parts produced using silicone liquid deposition modelling. These point clouds reflect the layer-by-layer evolution of the parts produced. A total of eleven parts were produced on four printing plates.

Silicone printing by liquid deposition modelling is sensitive to a number of faults, including: incorrect adjustment of the extrusion flow rate, part geometry, interaction between the extrusion nozzle and the printed part, and occlusion of internal structures.

Each printing palte contains parts enabling the manufacturing process to be tested against a defect that could lead to part destruction or manufacturing inaccuracies.

This dataset was used to put forward a method for monitoring silicone printing through indicators based on the segmentation and measurement of metrics on these point clouds. This dataset is offered to the community so that others can analyze the results of monitoring by other methods on these data acquired on real parts.

Details are provided in the file README.md

Matlab, 2023a

Identifier
DOI https://doi.org/10.57745/MKA5YJ
Metadata Access https://entrepot.recherche.data.gouv.fr/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.57745/MKA5YJ
Provenance
Creator Mosser, Loic ORCID logo; Barbé, Laurent ORCID logo; Rubbert, Lennart ORCID logo; Renaud, Pierre ORCID logo
Publisher Recherche Data Gouv
Contributor Barbé, Laurent; Université de Strasbourg; Institut national des sciences appliquées Strasbourg; Centre national de la recherche scientifique; Ecole de l'eau et de l'environnement; Entrepôt-Catalogue Recherche Data Gouv
Publication Year 2025
Funding Reference Agence nationale de la recherche ANR-22-EXOD-0005 ; Agence nationale de la recherche ANR-10-EQPX-44-01 ; Agence nationale de la recherche ANR-21-ESRE-0015 ; Agence nationale de la recherche ANR-22-CE10-0001
Rights etalab 2.0; info:eu-repo/semantics/openAccess; https://spdx.org/licenses/etalab-2.0.html
OpenAccess true
Contact Barbé, Laurent (ICube - UMR7357 ; CNRS, Université de Strasbourg, INSA Strasbourg, ENGEES ; France)
Representation
Resource Type Dataset
Format application/matlab-mat; text/markdown
Size 644100963; 5640
Version 1.0
Discipline Computer Science; Engineering Sciences; Construction Engineering and Architecture; Engineering
Spatial Coverage Laboratoire ICube (UMR 7357)