• Together, we applied advanced topology optimization to redesign critical brackets of the manipulator, achieving a 57–76% reduction in structural deflection.
• Our updated model also demonstrated a major stress decrease — from 93 MPa down to 25 MPa — all while staying within the allowed weight increase.
• Although we didn’t fully reach the target tip deviation of 0.3 mm (best achieved: 0.41 mm), the project gave us valuable insights and a solid foundation for the next design iteration.
🤔 Ready to build better AI models with synthetic data, but don't know where to start? Why go at it alone?💡
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🌟Mohana pavan Bezawada, @mohanapavan, who has risen in the ranks from the top 25 in the first competition all the way to top scorer in our current competition! His journey illustrates how dedication + Falcon can take you far in your AI journey.
🌟Nadia TRIKI, who delivered top-tier results in two of our recent Kaggle competitions and shared a detailed breakdown of her strategy - showcasing a deep command of AI training workflows and a commitment to helping others succeed.
Ángel Jacinto Sánchez Ruiz, @Sacus , who mastered FalconCloud to create targeted, high-performance datasets and provided crucial feedback and product requests that improved the data not only for him but for all of the current competitors.
🤩 Join our community today to partner with these super stars, and many more!