LAUSR

Abstract Three-dimensional printing (3D printing) technology based on slurry extrusion makes it possible to realize rapid manufacture of personalized, refined and complex ceramic products. The ceramic slurry for extrusion molding which is affected by various factors requires excellent extrusion properties and shape retention capacity. In this paper, the methods of orthogonal experiment design (OED) and back propagation artificial neural networks (BP ANNs) were combined to solve multi-objective and multi-factor problems caused by the preparation of alumina slurry. Through the combined model, the relationship between extrusion parameters and influencing factors of the slurry was obtained. The predicted optimal values were consistent with the experimental results, which proves the validity of the model. Alumina slurry suitable for 3D printing with excellent extrusion and shape retention properties was successfully prepared. The method is also applicable to the study of other multi-objective and multi-factor ceramic materials.