The problem

70% of steel production costs are attributed to raw materials. Scrap constitutes the largest portion of these costs.

Consequences of poor scrap management and classification:

The solution

A solution based on Artificial Intelligence has been developed, encompassing the following phases of the scrap entry process:

• Digitization of information generated in the truck entry workflow and management of the concept of a “digital record.”
• Preclassification of the scrap contained in the truck using “vision analytics.”
• Surveying the spatial profile of the truck’s cargo area and calculating volume and density using IoT technology.
• Classification of the scrap once unloaded in the designated unloading area.
• Integration of the chemical profile.
• Integration of the information and scaling of the digital record into the company’s ERP-MES.”

Benefits

The main benefits of digitizing the scrap entry process and adopting Industry 4.0 technologies such as Big Data, Artificial Intelligence, and IoT are:

• Reducing uncertainty and variability in classification.
• Streamlining the scrap entry process.
• Decreasing the potential for fraud in scrap entry.
• Ensuring data integrity across various departments and systems.
• Minimizing disputes over the quality of scrap.
• Gaining visibility and control over critical scrap characteristics.

Field Implementation