Predictive modeling of geometric deviations of 3D printed products - A unified modeling approach for cylindrical and polygon shapes

Geometric fidelity of 3D printed products is critical for Additive Manufacturing (AM) or 3D printing to be a direct manufacturing technology. Shape deviations of AM built products can be attributed to multiple variation sources such as substrate geometry defect, disturbance in process variables, and material phase change. Three strategies have been reported to improve geometric quality in AM: (1) control process variables x based on the observed disturbance of process variables Δx, (2) control process variables x based on the observed product deviation Δy, and (3) control input product geometry y based on the observed product deviation Δy. This study adopts the third strategy which changes the CAD design by optimally compensating the product deviations. To accomplish the goal an predictive model is desirable to forecast the quality of a wide class of product shapes, particularly considering the vast library of AM built products with complex geometry. Built upon our previous optimal compensation study of cylindrical products, this work aims at an unified modeling approach to predict the quality of both cylinder and polygon shapes. Experimental investigation of polygon shapes indicates the promise of predicting and compensating a wide class of products built through 3D printing technology.