This allows not only to increase production efficiency, but also to make the process more stable and predictable.
To obtain the exact amount of cast iron of the required quality with minimal fuel and energy costs, it is important to calculate the composition of the charge and know when and in what ratio it will enter the furnace. The main difficulty is that the chemical composition of the raw material is constantly changing, and its behavior in charge feeding areas in bunkers is uncertain.
Previously, the loading of a specific material into the furnace was determined by an approximate time frame. This made it difficult to accurately predict the composition of the outgoing stream. To solve this problem, NLMK has implemented a digital service that monitors the movement of raw materials and their chemical composition in real time along the entire path – from unloading to loading into the blast furnace.
When creating the service, DEM modeling was used, which allowed us to reproduce the mixing process and predict how the composition will change at the outlet. This model was combined with another one, the continuum model. It is based on mathematical formulas describing the physics of particle behavior.
To confirm the correctness of the data generated by mathematical models, NLMK has created a reduced physical prototype of a stationary bunker with transparent walls. It was he who made it possible to open one of the "black boxes". As a result, specialists were able to observe how the material inside the bunker behaves.
Then they began
Experiments on real equipment using RFID technology – when an object is identified using a radio signal. Raw materials with RFID tags were loaded along with the main stream, the tags were read both at the input and at the output. Additionally, lidar was used to scan the surface of the raw materials in the hopper.
The study showed that the actual movement of raw materials corresponds to digital models.
