Abstract
Ceramic on-demand extrusion (CODE) is a novel slurry-based additive manufacturing (AM) process for technical ceramics. Extensive characterization studies have shown that this process produces dense ceramic specimens with relatively improved mechanical properties such as flexural strength, fracture toughness, hardness, etc. The objective of the current study was to develop the next generation of CODE. The CODE printer created consists of an aluminum extrusion frame, a three-axis gantry system, an extruder, and a heat lamp. The ceramic slurry is fed to an extruder that prints parts onto a bedplate. The green body parts are then subject to postprocessing, including drying, debinding, and sintering. Ceramic composites and functionally graded materials are created using CODE to further study the process. Furthermore, a real-time deep learning defect detection protocol to identify common defects of CODE while printing, as well as a control feedback system to implement corrective action based on the defect detected, is being developed.
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