Large-scale additive manufacturing offers the potential to revolutionize various industries by enabling the fabrication of intricate and massive structures that were previously difficult or costly to produce. However, the trade-off between printing speed and print quality remains crucial in this field. As the printing speed increases, there is often a compromise in the final object's surface finish, accuracy, and structural integrity. Our goal is to balance the need for rapid production with the desire for high-quality results to unlock the full potential of large-scale additive manufacturing for applications ranging from construction to aerospace.
Continuous printing, also known as video projection Stereolithography, is recognized for its rapid, cost-effective, and high-resolution capabilities in additive manufacturing (AM). However, it has encountered significant challenges, such as manufacturing defects like voids within the solid geometry and manufacturing limitations related to size constraints.Â
This project introduces a novel approach termed gradient light video projection-based stereolithography (GLVP-SL) coupled with continuous resin flow to address these issues. This innovative AM technique facilitates the seamless creation of three-dimensional (3D) solid objects based on the principle of finely regulating exposure energy. Unlike the conventional approach of employing a single image per layer, the GLVP-SL method incorporates three mask images for each layer, each possessing distinctive grayscale distributions. The influence of these grayscale distributions on printing process parameters, such as curing speed and resin flow, is systematically explored. The study further devises an optimization model to determine the optimal grayscale distribution pattern to achieve the desired macroscale size, density, and surface quality of the solid structure.
To provide a comprehensive assessment, a range of solid objects were produced using both the conventional VP-SL process and our proposed GLVP-SL process. The printed parts were subject to evaluation of porosity and surface roughness. These experimental findings validated the capability of the GLVP-SL process to generate large-area 3D solid objects with enhanced surface quality.