Feasibility Study of AI-Driven Image-Based Dimensional Metrology for Powertrain Manufacturing – AI-MetPower
| Reference number | |
| Coordinator | Kungliga Tekniska Högskolan - Institutionen för Produktionsutveckling |
| Funding from Vinnova | SEK 516 000 |
| Project duration | May 2025 - February 2026 |
| Status | Ongoing |
| Venture | Circularity - FFI |
| Call | Circularity - FFI - spring 2025 |
Purpose and goal
This pre-study aims to assess the feasibility of AI-driven image-based dimensional metrology in powertrain manufacturing. It seeks to evaluate accuracy, explore integration challenges, and address technical issues like image quality and algorithm accuracy. The goal is to lay groundwork for future full-scale implementation, enhancing precision and efficiency in manufacturing.
Expected effects and result
Successful implementation of AI-driven image-based metrology will redefine quality assurance, benefiting manufacturers, consumers, and the industry. It enhances circular manufacturing by improving precision, efficiency, and sustainability. AI metrology minimizes waste by identifying defects early, supporting remanufacturing and recycling, leading to cost savings and improved product quality.
Planned approach and implementation
The project is divided into three phases: Conceptual Framework Development (WP2, WP3), Technical Evaluation (WP3, WP4), and Impact Assessment (WP5). It includes 5 work packages: Project Management, Feasibility Assessment, Dataset Requirements, Algorithm Development, and Dissemination. This structured approach ensures thorough investigation and clear deliverables.