Quality Assurance and Efficiency Enhancement for Stereolithography-based 3D and 4D Printing

The emergence of additive manufacturing (AM), also referred to as 3D printing, has provided the potential to revolutionize the manufacturing sectors with shorter product development cycles, fewer materials wastes, and more product design and fabrication freedom. Recently, an increasing interest has been closely associated with AM and made it a mainstream manufacturing process leading to rapid growth in the global AM market. Consequently, extensive research efforts have been dedicated to advancing the development of AM and supporting its deployment. Particularly, recent advancement in AM has broadened its applications from rapid prototyping and tooling to rapid manufacturing of functional parts used in a wide range of industries such as aerospace, automobile, and consumer products. The current AM applications are mainly limited to small-sized, low-volume production. To further increase the utilization of AM technologies, it is critical to investigate and improve the fabrication quality and process efficiency. To facilitate the wide adoption of AM techniques for various potential applications and provide valuable insights to AM users and manufacturers, this dissertation is conducted to promote quality assurance of AM products and efficiency improvement for AM systems. More specifically, mathematical models are established to quantify the impacts of printing and post-curing parameters on the resulting mechanical behavior. The established models can be applied to aid the selection of process parameters in 3D printing and associated post-curing processes. In addition, the emerging shape memory property is theoretically modeled and characterized under cyclic thermo-mechanical conditions, when the thermo-responsive material is adopted for printing. Adopting the established models can improve the shape memory quality and aid enhance the cyclic durability of the 4D printed parts. Moreover, an efficiency-aware curing approach is proposed to predict and reduce the total build time considering several quality aspects. The proposed method is experimentally examined for its effectiveness in enhancing printing efficiency while ensuring product quality in terms of geometric dimensions, mechanical property, and surface finish. The outcomes of this dissertation will positively contribute to AM process planning and strengthen the understanding of quality assurance and efficiency enhancement in AM.