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Project # 61
Advanced Sensing and Machine Learning for Wire-Arc Additive Manufacturing Optimization toward Improved Quality and Energy Efficiency
| Team Lead: | Karan Rajendra Saraswat |
| Other Team Members: | Jonathan Hernandez | Amogh Modgekar Desai | Zayan Aly |
| Faculty Advisor(s): | Dr. Chen Kan |
| Department: | IMSE |
| Project Type: | REU |
| Title: | Advanced Sensing and Machine Learning for Wire-Arc Additive Manufacturing Optimization toward Improved Quality and Energy Efficiency |
| Abstract: | With its high material deposition rate and scalability, wire-arc additive manufacturing (WAAM) has been increasingly used in manufacturing and re-manufacturing large-scale structural components. However, a critical concern hinders its broader adoption – defects commonly arise in WAAM due to factors like arc instability and uneven cooling. To advance the field of WAAM, this project proposes a new framework that leverages advanced sensing and machine learning for defect detection and process optimization of WAAM. The developed tools have great potential to be extended to a wide variety of metal-based AM processes across diverse applications. |
| Poster: | View Poster #61 (PDF) |
| Judges Scoring: | Submit Evaluation (judges only) |