AI‑based decision support for resilient material supply in Swedish foundries

Purpose and goal

The goal is to develop methods and tools to handle variations in material composition and create a more resilient and circular material flow. The aim is to ensure the right quality and properties in the castings even with varying raw materials, while reducing climate impact and strengthening competitiveness. The long-term aim is a resource-efficient, circular and resilient foundry process through improved material management and AI-based decision support for the melting process.

Expected effects and result

The project develops AI-based decision support for data-driven decision-making in foundry processes. This increases resource efficiency and improves process stability while strengthening expertise. A common digital decision support improves coordination and decision-making along the value chain. The project contributes to a technological shift that strengthens competitiveness, reduces climate impact through increased use of recycled materials and promotes modern and attractive work environment.

Planned approach and implementation

The project is carried out in close collaboration through meetings, workshops and company visits. It includes a current situation analysis and process mapping, followed by data collection and feasibility analysis. AI models are developed and trained for recipe generation and resource allocation, and are then integrated, verified and demonstrated in an industrial environment. Results are disseminated internally through project activities and externally through industry channels and publications.