Professor Fan Mo Brings an “Adaptive Soul” to Intelligent Manufacturing at WAIC 2026

From Cambridge to Chengdu: Professor Fan Mo Brings an “Adaptive Soul” to Intelligent Manufacturing at WAIC 2026

At WAIC 2026, Professor Fan Mo of UESTC presented “Manufacturing the Future: Machine-Learning-Driven Real-Time Process Control and Adaptive Production,” outlining a framework for production lines that can sense, reason and evolve.

Machine Learning Reconstructs the Production Chain

Professor Mo introduced real-time process control, predictive maintenance and adaptive production scheduling. In a semiconductor collaboration, the process-control system improved yield by 12 percent and reduced energy use by 30 percent.

Predictive maintenance analyzes vibration, temperature and current data to provide early warnings, reducing unplanned downtime by up to 45 percent. A deep-reinforcement-learning scheduling system improved on-time delivery from 78 percent to 94 percent in an automotive-parts factory.

The presentation and exhibition attracted professionals from industry and academia.

Explainability: the Bridge from Theory to Engineering

Professor Mo emphasized that frontline engineers must understand and trust AI recommendations. His team’s explainable-machine-learning framework preserves predictive accuracy while producing understandable decision rationales, and has been validated with manufacturing partners.

Cambridge DNA and Chinese Practice

Cambridge’s responsible-innovation ethos and practical engagement with China’s manufacturing transformation are helping to advance the next AI-for-Manufacturing paradigm.