Tomographic projection optimization for volumetric additive manufacturing with general band constraint Lp-norm minimization
Chi Chung Li, Joseph Toombs, Hayden Taylor, Thomas J. Wallin
Abstract
Tomographic volumetric additive manufacturing is a rapidly growing fabrication technology that enables rapid production of 3D objects through a single build step. In this process, the design of projections directly impacts geometric resolution, material properties, and manufacturing yield of the final printed part. Herein, we identify the hidden equivalent operations of three major existing projection optimization schemes and reformulate them into a general loss function where the optimization behavior can be systematically studied, and unique capabilities of the individual schemes can coalesce. The loss function formulation proposed in this study unified the optimization for binary and greyscale targets and generalized problem relaxation strategies with local tolerancing and weighting. Additionally, this formulation offers control on error sparsity and consistent dose response mapping throughout initialization, optimization, and evaluation. A parameter-sweep analysis in this study guides users in tuning optimization parameters for application-specific goals.