How AI Will Support
HTS Manufacturing
at Renaissance Fusion

Grenoble, France, 17 September - At Renaissance Fusion we have successfully deployed the first phase of the Data & AI roadmap.

Connected to our HTS pilot line, a new data platform now makes key production data accessible through dedicated dashboards, providing teams greater visibility into manufacturing operations and laying the foundation for future AI applications.

This is more than a technical milestone. It marks an important step toward the industrialization of HTS manufacturing.

"The first benefit is visibility," explains Alessandro Giassi, Data & AI Expert. "By collecting and visualizing production data in near-real time, teams gain a much better understanding of how the line is operating and can detect trends or anomalies more quickly."

Production data is collected every second and structured to support both operational monitoring and future AI-powered analytics.

For Marion Hudson, Head of Technical Project Delivery, the initiative is particularly important given the stringent quality requirements of HTS manufacturing.

"By transforming complex production data into actionable insights, the platform supports both operational excellence and strategic decision-making throughout the manufacturing lifecycle."

The platform has been designed to do much more than support dashboards. The long-term ambition is to leverage growing datasets for high-value use cases such as process optimization, yield improvement and predictive maintenance.

"Our vision is to progressively move from descriptive analytics to AI-powered capabilities," says Giassi. "First, helping engineers identify the root causes of defects. Then becoming predictive, for example by anticipating equipment failures before they occur. Ultimately, we want to become prescriptive, using AI and optimization techniques to recommend the best operating conditions to improve performance, quality and yield."

This achievement is the result of a truly cross-functional effort, bringing together:

✅ IT, which built the data platform foundations.

✅ Automation & Control, which enabled data acquisition from the production environment.

✅ HTS teams, which defined the operational requirements and expected outcomes.

✅ Data & AI, which designed the architecture and long-term analytics roadmap.