A Study on Automated Quality Control and Improvement Using Advanced Monitoring Sensors by AI in Continuous Casting
| Reference number | |
| Coordinator | SWERIM AB |
| Funding from Vinnova | SEK 525 000 |
| Project duration | August 2021 - May 2022 |
| Status | Completed |
| Venture | The strategic innovation programme for Metallic material |
| Call | Springboard to the metallic materials of the future - Step 1 |
Important results from the project
SMART-CAST in the 1st stage aimed to study merging advanced monitoring systems including mould temperature sensors and strand surface monitoring systems through AI models to increase the process flexibility and efficiency during casting of advanced steel grades such as stainless and wear resistance grades. The current feasibility study is necessary to investigate the main process challenges, surveying emerging technologies, assessing possible sensors from suppliers as well as implementation cost for such an approach.
Expected long term effects
The project brings new opportunities for real-time monitoring of CC. The project led to the following deliverables: Mapping of current technologies in monitoring and control of heat transfer and product quality in CC. Investigation of AI algorithms with special attention to process control. Data exchange between sensors; finding requirements to merge data streams from sensors with AI. Future partners, cost estimation and required resources for a fullscale project. Moreover, the project led to a full-scale application submitted to VINNOVA on 15th June 2022.
Approach and implementation
The project has been implemented in 3 main WPs as follow: WP 1 Studying the benefits of merging the monitoring technologies WP2 Proof-of-Concept (POC) of AI algorithms for process optimization WP3 Data exchange between sensors and AI