Force-based adaptive deposition in multi-axis additive manufacturing: Low porosity for enhanced strength

Abstract

Multi-axis additive manufacturing enhances mechanical strength by aligning printed layers with principal stress directions. However, this benefit introduces a key challenge: non-uniform layer thickness becomes inevitable due to surface curvature and deposition angle variations. Moreover, unpredictable errors in material deposition – such as inaccurate extrusion control, collapse of earlier deposited layers, or machine malfunctions – can accumulate throughout the build. These issues are difficult to model accurately in advance, making purely offline planning impractical for ensuring consistent print quality, especially in complex geometries. To address this issue, we propose a force-based adaptive deposition method that actively minimizes porosity during filament-based multi-axis AM. Our closed-loop control strategy dynamically adjusts the printhead’s motion speed based on real-time force feedback, while maintaining constant extrusion speed. Unlike geometry-driven offline planning approaches, our method compensates for thickness variation and process uncertainties, resulting in improved filament bonding. Experiments show up to a 72.1% increase in failure load compared to baseline methods, with similar or lower part weights. The approach also enhances robustness against extrusion irregularities, ensuring more consistent mechanical performance.