High-Speed Alumina Stereolithography

Abstract

The additive manufacturing of ceramics offers a reliable and repeatable method for fabricating parts with complex geometries. To compete with conventional ceramic forming methods, the time and cost associated with material and process optimization for ceramic stereolithography should be improved. Computational analysis methods can be utilized to reduce the number of experimental steps required for material and process optimization. This work used the discrete element method and ray tracing analyses to predict suitable material parameters and processing conditions for ceramic stereolithography. The discrete element method was used to create alumina particle dispersion models to predict suitable paste compositions, and ray tracing was used to predict suitable laser power and scan speed to achieve a sufficient curing depth for stereolithography processing. The predicted conditions of paste composition and processing parameters were comparable to experimental values, reducing the number of experimental iterations required for process optimization. Furthermore, suitable processing parameters for high-speed fabrication by stereolithography was predicted, achieving a processing speed much faster than previously reported ceramic stereolithography. The reduction in process optimization timeline, and the increase in fabrication speed, could increase the appeal of ceramic stereolithography to industry.