Development of a digital twin system for constructing rough surface of models in light-curing additive manufacturing

Abstract

Light-curing additive manufacturing is extensively employed in high-precision industries due to its capability to generate products with exceptional surface quality. Nonetheless, given the susceptibility of the surface of light-curing additive manufacturing models to various factors, the current model is constructed based on design parameters, which may not precisely replicate the actual model surface. This constraint hampers the analytical work across various stages. Moreover, distinct analysis stages may necessitate varied physical models. While it is feasible to produce corresponding models for each stage, this approach may result in time wastage and reduced efficiency. To address this issue, this paper introduces a digital twin system for light-curing additive manufacturing, incorporating an integrated algorithm specifically designed for constructing rough surfaces. The algorithm employs the Fast Fourier Transform (FFT), Johnson Transformation System, and autocorrelation Function to generate the surface topography of the model. Additionally, the system can monitor the printer’s stability throughout the printing process. To validate the feasibility of this system, a DT system was implemented to monitor the printer’s stability throughout the printing process and construct the surface topography of the printed model. The surface of the physical model was measured using a 3D surface profiler and perform statistical analysis of the model surface data. Finally compared with the rough surface constructed by the DT system. The results indicate that the characteristic parameter errors of the model surface are all below 5%, providing evidence that the rough surface constructed by the system fulfills the specified requirements.