Denture reinforcement via topology optimization

TL;DR

This paper introduces a computational topology optimization method to strategically reinforce dentures, significantly reducing displacement and guiding efficient reinforcement placement for improved durability.

Contribution

It presents a novel topology optimization approach for denture reinforcement, enabling automated, material-efficient placement of reinforcement in 3D-printed dentures.

Findings

Reinforced dentures show decreased displacement compared to non-reinforced ones.

Topology optimization effectively identifies regions needing reinforcement.

The method aids dental technicians in efficient reinforcement placement.

Abstract

We present a computational design method that optimizes the reinforcement of dentures and increases the stiffness of dentures. Our approach optimally places reinforcement in the denture, which modern multi-material three-dimensional printers could implement. The study focuses on reducing denture displacement by identifying regions that require reinforcement (E-glass material) with the help of topology optimization. Our method is applied to a three-dimensional complete lower jaw denture. We compare the displacement results of a non-reinforced denture and a reinforced denture that has two materials. The comparison results indicate that there is a decrease in the displacement in the reinforced denture. Considering node-based displacement distribution, the reinforcement reduces the displacement magnitudes in the reinforced denture compared to the non-reinforced denture. The study guides dental technicians on where to automatically place reinforcement in the fabrication process, helping them save time and reduce material usage.