Url https://www.cimne.com/sgp/rtd/Project.aspx?id=906
Acronym PriMuS
Project title Printing pattern based and MultiScale enhanced performance analysis of advanced Additive Manufacturing components
Reference PID2020-115575RB-I00
Principal investigator Luis Miguel CERVERA RUIZ - mcervera@cimne.upc.edu
Narges DIALAMISHABANKAREH - narges@cimne.upc.edu
Start date 01/09/2021 End date 31/08/2024
Coordinator CIMNE
Consortium members
Program P.E. de I+D+i Orientada a los Retos de la Sociedad Call Proyectos de I+D+i 2020
Subprogram Retos Investigación Category Nacional
Funding body(ies) MCIU Grant 133.100,00 €
Abstract Additive Manufacturing (AM), also known as 3D printing, is a technique to fabricate parts and components from a Computer-Aided Design (CAD) model. This is done through layer-by-layer deposition of different materials ranging from polymers to metals, as well as cementbased compounds. Polymer-based 3D-printing is evolving fast, moving the focus from rapid-prototyping to the fabrication of structural components with enhanced thermal resistance as well as mechanical strength while reducing weight and material use. Acrylonitrile butadiene styrene (ABS), polycarbonate (PC) and polylactic acid (PLA) are some examples of polymer-based materials commonly used in AM processes. The PriMuS project focuses on one of the first AM techniques, well established for polymeric materials: FDM, also called Fused Filament Fabrication (FFF). Of all the AM techniques available today, FFF is the best known and the most widely used due to its versatility and suitability for operating with a wide range of materials. FFF is based on the extrusion of the printing material through a nozzle to reproduce a 3D CAD model. The deposition process is carried out by melting the filaments of a certain thermoplastic material. The extruded material is deposited layer by layer on a printing table. Simultaneous movements of the nozzle and the printing table allow the deposition in 3D, thus enabling the system to manufacture complex 3D geometries. PriMuS will develop a computational tool for the predictive analysis of the performance of thermoplastic components manufactured via FFF. PriMuS will be based on the actual printing patterns and on multiscale techniques, aiming at representing the mechanical response of complex in-fill and lattice inner structures at a viable computational cost. Design and development of advanced additive manufacturing components employing the particular features of auxetic structures will be also considered. Performing virtual tests using PriMuS will accomplish significant design improvements characterized by I) enhanced energy efficiency, ii) raw material use reduction, iii) on-request production. Decision-making based on Machine Learning (ML) will be incorporated in the computational tool to estimate the process parameters that will ensure the optimized mechanical performance. Overall, PriMuS will facilitate the wider adoption of FFF technology as an industry-accepted manufacturing process. The specific objectives of PriMuS are: - To design and develop a FFF-AM rapid prototyping module for the performance analysis of advanced FFF components. - To design and implement failure criteria for the detection of failure in the printed components. - To implement a multiscale approach based on Reduced Order Modeling (ROM) techniques for characterization of the FFF parts. - To enable Machine Learning for the optimization of FFF process parameters and development of 3D modelling components. - To design and implement modeling component based on auxetic structures: Advanced Additive Manufacturing Components - To measure the quality of the FFF-AM module in terms of technical performance; Integration of the prototype system and testing - To validate and demonstrate the ability of the FFF-AM module in real life biomedical demonstrators.
Proyecto PID2020-115575RB-I00 financiado por MCIN/ AEI /10.13039/501100011033