A digital process was developed to facilitate additive manufacturing for ceramic materials using digital light processing (DLP). A numerical model that predicts DLP sample properties can be generated from manufacturing inputs to forecast the effect of resin age on mechanical strength of the printed part based on data collected from experiments. Key parameters for printing the green bodies included determining the depth of cure, layer thickness, material composition, and solids loading. Thermogravimetric analyses were used to develop debinding and sintering curves. Debinding is used to remove the volatile organics comprising the photopolymer resin. Sintering is performed after debinding to increase density and mechanical strength of the printed parts. The sintered parts were then subjected to characterization and mechanical testing. The ensemble of data for various DLP-printed ceramic materials were added to a database. A design of experiments can be generated from the manufacturing process defined in the database with selected changeable parameters randomized over a range. Because the database is defined with an architecture to capture manufacturing processes, it can persist as a more generic platform for manufacturing digital twins. This can ease the development of future digital twins and can grow as a common repository for the insights gained from manufacturing research. Creating a digital twin of a DLP system for 3D printing parts enables manufacturers to simulate and assess the impact of resin age on printing parameters and part quality, facilitating optimization, predictive maintenance, and cost reduction.
Read full abstract