Instrumentation of silicone liquid deposition modeling by extrusion: Introduction and evaluation of laser profilometry and associated indicators for supervision
Year: 2025
Type: article
Abstract: While silicone printing by extrusion is a promising technique, part production is still a challenge when support-free printing is considered. In this paper, we consider three main causes of defects, namely the management of silicone flow rate during printing, the part deformation under its own weight before polymerization and the deformations due to the nozzle-layer interactions during printing. An instrumentation strategy is here proposed to monitor layer deposition. Our approach, based on laser profilometry, is detailed with open source software to control printing and scanning. The process to build point clouds and extract data is presented. More importantly, indicators are introduced to build metrics related to the current main causes of printing failure, using prior geometric information on the planned layers. Through experimental evaluation, the adequacy of the indicators and their complementarity is discussed. This introduction of new indicators opens ways to implement efficient silicone extrusion supervision. • Silicone extrusion is sensitive to flow rate, part weight and nozzle interaction. • Laser profilometry is proposed with 3 specific indicators to monitor the process. • Experimental assessment validates relevance of laser profilometry for monitoring. • Open source code is provided for future supervision development and instrumentation.
Source: Additive manufacturing
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,430
Funder: Agence Nationale de la Recherche
Awards: G1145502871, G3441976835, Infrastructure technologique pour la recherche d’excellence en robotique, Réseau national de plateformes robotiques d'excellence, Robotized Additive Manufacturing for Silicone assisted by an Artificial Intelligence, Material, Architecture & Embodied Intelligence, G693040958, G7240651115, G8510727784
OpenAlex ID: W4409760841
