Improved Height Difference Algorithms for Enhanced Accuracy in Drop-on-Demand 3D Printing with UV-Curable Inks

Abstract

Drop-on-demand (DoD) 3D printing with UV-curable inks offers precision in fabricating intricate geometries, but achieving consistent layer heights remains a significant challenge. Variations in droplet behavior, curing dynamics, and substrate interactions can lead to inaccuracies, impacting the quality and resolution of printed components. This study presents an improved height difference algorithm designed to enhance the accuracy of layer height deposition in DoD 3D printing. The algorithm integrates real-time feedback on droplet impact, spreading, and curing processes, utilizing advanced predictive modeling and machine learning techniques to adjust inkjet parameters dynamically. Experimental validation demonstrates significant improvements in surface uniformity and dimensional accuracy, particularly in complex geometries and high-resolution applications. Additionally, the approach reduces material waste and enhances print speed by optimizing droplet placement and curing efficiency. The findings highlight the potential of the proposed algorithm to advance DoD 3D printing with UV-curable inks, paving the way for applications in electronics, bioprinting, and high-precision manufacturing.

Cite as:

Adeoye Ibrahim, & Kayode Sheriffdeen. (2025). Improved Height Difference Algorithms for Enhanced Accuracy in Drop-on-Demand 3D Printing with UV-Curable Inks. Research and Reviews: Journal of Mechanics and Machines, 7(1), 1–8.

https://doi.org/10.5281/zenodo.14587391