In steelmaking, the raw material costs can be as high as 80 % of the overall production costs, depending on the steel grade type and alloy content. Our raw material mix optimization algorithm can help find material mixes that allow for the maximum reuse of the alloy content of raw materials with the minimum cost.
Intelligent algorithms not only consider the amount of valuable alloying elements in raw materials, but also account for metallurgical processes and effects on these alloying elements. By using an unprecedented multilevel optimization algorithm, we can make proposals for optimized material mixes that reduce our customer’s input material cost by up to 35 %.
How it works
At its core, our material mix optimization algorithm (MMOA) is just plain mathematics. However, by combining it with an in-depth understanding of metallurgical reactions and processes, we have augmented this algorithm to present an intelligent, multi-level optimization for the melting and refining phases of liquid steelmaking.
The considered metallurgical parameters are:
- Material mass, material efficiency and material bulk density
- Material availability and mass constraints
- Chemical mix analysis of each material
- Chemical and process efficiency of each element
- Oxidation and reduction reactions between metal phase and slag phase including slag efficiency
- Target volumes or mass and respective constraints
- Under development: temperature-dependency of oxidation and reduction reactions