Towards a digital twin of extrusion-based additive manufacturing: an experimentally validated numerical model of ironing process

Abstract A numerical framework was developed to optimize ironing post-processing parameters to reduce porosity and manufacturing time while enhancing shape accuracy and ultimate tensile strength (UTS) of 3D printed polylactic acid (PLA) parts. The material extrusion (MEX) additive manufacturing of a top layer consisting of three adjacent strands was simulated using multiphase non-Newtonian computational fluid dynamics (CFD) under different values of extrusion temperature, layer height, and strand overlap. Simulations revealed that a 50% strand overlap prevented porosity, while a 25% overlap led to significant porosity, particularly at lower extrusion temperatures and higher layer heights. In this regard, ironing was identified as an effective post-processing technique. Therefore, numerical and experimental investigations have been done with respect to 25% strand overlap: ironing line spacing (LS) significantly influences porosity, while ironing speed (IS) affects manufacturing time. Higher ironing LS and IS yielded the best results at low layer heights, while a balanced approach optimized ironing at higher layer heights, resulting in a reduction up to 31.97% in overall manufacturing time if compared with traditional approach (i.e., lower values of ironing LS and IS). UTS improved by up to 21.49%, underscoring ironing impact on the final properties of PLA parts. The accuracy of the proposed CFD model is expected to lay the foundation for a reliable digital twin of MEX, improving part quality and reducing manufacturing costs and waste.