Stress-Guided Material Segmentation for Recycled 3D Printed Structures Using Finite Element Analysis

Abstract

We present a simulation-driven method for optimizing the structural performance of 3D printed objects made with recycled and fresh filament. Although sustainable materials such as recycled PLA reduce environmental impact, they often exhibit degraded or inconsistent mechanical properties, making them less suitable for structurally demanding applications. To address this, we develop a finite element analysis (FEA) pipeline that simulates stress and strain distributions under user-defined loading conditions, enabling intelligent segmentation of the object into regions of high and low mechanical demand. These segmented regions can be assigned recycled or fresh material during fabrication. Our system leverages open-source tools (SfePy) for simulation and we validate its accuracy against Abaqus, a commercial industry standard. We also introduce methods for automatically identifying and correcting segmentation artifacts, such as small disconnected islands. Through comparative simulation studies and performance evaluation, we demonstrate that our approach enables more sustainable 3D printing without sacrificing structural reliability