RAMSAI

The factory of the future must ensure flexible, reliable and efficient production. For the production of silicone parts, widely used in industry, current processes based on molding and injection techniques do not meet these requirements. Additive manufacturing (AM) should overcome these problems. However, the rheological behavior of silicone as a flexible material during deposition is complex and difficult to model. Conventional additive manufacturing strategies, using deposition strategies which are adjusted off-line with a priori knowledge models, find their limits. In the RAMSAI project, we propose to develop a new approach to AM by exploiting artificial intelligence to control the rheological behavior of silicone during extrusion. The work will be multidisciplinary, combining material science, mechatronics, artificial intelligence, and robotics. A new silicone printing head integrating rheological control of the silicone and dimensional control of the filament will be developed. The closed-loop control of silicone rheological behavior will use physics-based machine learning and predictive algorithms. The filament dimensions will be controlled using a variable shape nozzle already developed by the project partners. For complex parts, the contribution of a control of the print head in position and orientation using a robotic arm will be determined. These scientific and technological developments will lead to the realization of demonstrators which will highlight the new performances of the process. The first application area targeted will be health care, with a proven need today for tools to produce patient-specific realistic anatomical models for training and planning surgical interventions.