Point Cloud Data for Silicone Liquid Deposition Modeling

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