CircuVision: AI-Driven Process Assurance
| Reference number | |
| Coordinator | RISE Research Institutes of Sweden AB |
| Funding from Vinnova | SEK 499 854 |
| Project duration | June 2026 - January 2027 |
| Status | Ongoing |
| Venture | Circularity - FFI |
| Call | Cirkularitet FFI – spring 2026 |
Purpose and goal
The project´s aim is to validate the technical feasibility of capturing diagnostic data via AI-driven computer vision in manual manufacturing processes, and to automatically transfer this data to manufacturing execution systems (MES) and digital battery passports (DBP). The objectives include establishing requirements for assembly, repair and disassembly. Furthermore, test stations will be explored to evaluate AI models for defect detection, and a roadmap will be developed for a demonstrator.
Expected effects and result
The project addresses FFI Circularity´s focus areas of the Production System and the Product. By creating a link between physical processes and digital documentation, Design for Circularity is enabled, which facilitates the assessment of the residual value of batteries. Environmental impacts include reduced scrap during repair and secured material flows during disassembly. This increases the resilience of material supply and contributes to a safer working environment for operators.
Planned approach and implementation
The feasibility study will last about nine months and is being run by a consortium consisting of RISE, Scania IB and SICK. The implementation is structured in three work packages (WP). WP1 includes AI-based process assurance, establishment of test stations and evaluation of computer vision. WP2 aims to develop a digital transmission prototype for diagnostic data between MES and DBP. WP3 focuses on project management and the development of a full-scale demonstrator project.