This article is based on insights from an interview with Yann Cochard, who shares perspectives on the current status, challenges, and future direction of the Michelin pilot within the SEISMEC project.
Within SEISMEC, Michelin is developing an AI-based task recommender application designed to support workers operating complex industrial equipment. The system provides real-time task scheduling and helps operators anticipate upcoming actions, while also offering decision-support tools for automated machinery. Rather than replacing human input, the application is designed to keep workers in control, combining automation with operator expertise to improve flexibility, responsiveness, and efficiency on the factory floor.
A central aspect of the pilot is its strong human-centred approach. Development is grounded in on-site immersion and direct engagement with workers, ensuring that solutions are shaped by real operational needs. The process is iterative and feedback-driven, allowing continuous refinement of the technology based on user experience. One of the key challenges has been ensuring that the system remains relevant and practical in complex, fast-changing industrial environments, where usability and trust are essential for adoption.
The Michelin pilot aims to scale the solution beyond initial use cases, extending it across different machines, products, and a broader community of workers. By continuing to prioritise worker empowerment and involvement, the pilot demonstrates how AI can be integrated into industrial settings in a way that strengthens skills, supports decision-making, and enhances overall working conditions.