Controlled Ca addition by Usage of OES-PDA Technology

Purpose and goal:

The project’s main goal was to explore ways to utilize OES-PDA technology to dynamically manage the Ca additions while enhancing process control. Additionally, the project aimed to detect and categorize unintentional inclusions in materials for critical applications linked to impurities in alloying additions at an early stage. The study concludes that the OES-PDA technique can provide information about the results of calcium treatment and identify minute amounts of trace elements in the inclusions.

Expected results and effects:

The OES-PDA technology can potentially improve steel quality and enhance process control in steel production. However, exploring how unit operations impact the inclusions and how they can be controlled is necessary. Once this is thoroughly studied, an AI model can be created to monitor and adjust the additions dynamically.

Additionally, the study revealed that more data (more burn spots) is required to obtain reliable and representative images of the entire steel melt containment. This requires further investigation. By doing so, steel manufacturing can become more effective. Approach and implementation:

The project involved collaboration between Swerim, Jernkontoret, and five Swedish steel manufacturers. Trials were conducted at four steel plants, and the data collected through OES-PDA technology was linked to process parameters. The project explored the potential of using machine learning and self-learning algorithms (AI) to enable OES-PDA technology for process control.

The potential of using this technology to dynamically control the addition of Ca in ongoing production and identify inclusions affected by impurities in alloying properties at an early stage was evaluated.