| About this Abstract |
| Meeting |
2022 TMS Annual Meeting & Exhibition
|
| Symposium
|
REWAS 2022: Automation and Digitalization for Advanced Manufacturing
|
| Presentation Title |
Refractory Lifetime Prediction in Industrial Processes with Artificial Intelligence |
| Author(s) |
Nikolaus Voller, Christoph Pichler, Christine Wenzl, Gregor Lammer |
| On-Site Speaker (Planned) |
Nikolaus Voller |
| Abstract Scope |
This paper deals with refractory lifetime prediction by using artificial intelligence (AI). Through the effective use of process parameters, obtained from various operational processes within the Industrial (Cement/Lime, Non-Ferrous Metals, Process Industries, Foundry) and Steel sector, an AI model is generated. With the assistance of modern surveying technology, a correlation can be identified between process parameters and refractory wear. Using this method, suitable prediction of the refractory lifetime, as well as the wear mechanism, is possible. In addition, maintenance cycles can be adjusted and the optimal maintenance intensity of the operated furnaces can be ensured. With our intelligent Automated Process Optimization (APO) solution the prediction of refractory lifetime and wear mechanism can be done in real-time. Thus, we can provide value-added service to our customers. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Pyrometallurgy, Ceramics, Machine Learning |