Automatic exposure volumetric additive manufacturing

TL;DR

This paper introduces an automated, real-time exposure control system for tomographic volumetric additive manufacturing that significantly improves print fidelity, repeatability, and generalizes across various geometries, surpassing traditional manual methods.

Contribution

We developed a robust auto exposure routine using real-time light scattering data, enabling accurate, repeatable, and human-independent volumetric 3D printing.

Findings

Auto exposure VAM achieves high fidelity and repeatability.

The method generalizes well to diverse geometries.

Print accuracy can surpass commercial resin 3D printers.

Abstract

Tomographic volumetric additive manufacturing (VAM) achieves high print speed and design freedom by continuous volumetric light patterning. This differs from traditional vat photopolymerization techniques that use brief sequential (2D) plane- or (1D) point-localized exposures. The drawback to volumetric light patterning is the small exposure window. Overexposure quickly leads to cured out-of-part voxels due to the nonzero background dose arising from light projection through the build volume. For tomographic VAM, correct exposure time is critical to achieving high repeatability, however, we find that correct exposure time varies by nearly 40% depending on resin history. Currently, tomographic VAM exposure is timed based on subjective human determination of print completion, which is tedious and yields poor repeatability. Here, we implement a robust auto exposure routine for tomographic VAM using real-time processing of light scattering data, yielding accurate and repeatable prints without human intervention. The resulting print fidelity and repeatability approaches, and in some cases, exceeds that of commercial resin 3D printers. We show that auto exposure VAM generalizes well to a wide variety of print geometries with small positive and negative features. The repeatability and accuracy of auto exposure VAM allows for building multi-part objects, fulfilling a major requirement of additive manufacturing technologies.