About this Abstract |
| Meeting |
2026 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2026)
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| Symposium
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2026 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2026)
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| Presentation Title |
Residual Stress-Informed Slicing Optimization for Multi-Laser Powder Bed Fusion |
| Author(s) |
Ronnie Frank Pires Stone, Tianyu Gao, Rongxuan Wang, Zhenghui Sha |
| On-Site Speaker (Planned) |
Ronnie Frank Pires Stone |
| Abstract Scope |
Multi-laser powder bed fusion (ML-PBF) is an established additive manufacturing technology adopted in industrial applications due to its capability to fabricate complex geometries with high precision. However, predicting the quality of manufactured parts remains a significant challenge, particularly for emerging material systems such as advanced metals and ceramics that require new process characterization. The difficulty arises from the complex thermo-mechanical physics governing the process, where localized melting and sintering between laser scan tracks strongly influence residual stress formation and final part integrity. Accurately simulating residual stress evolution and the effects of multi-laser path strategies is computationally expensive, limiting the practicality of high-fidelity approaches for design optimization and process planning. In this work, we present an optimization framework based on a lightweight computational model for residual stress prediction in ML-PBF. We demonstrate that the proposed framework achieves strong agreement with physical experiments while offering significant computational advantages compared to state-of-the-art methods. |
| Proceedings Inclusion? |
Undecided |