To manufacture more than 5 million tonnes of steel annually and deliver each order just in time, the Hüttenwerke Krupp Mannesmann (HKM) plant must operate on a tightly controlled schedule. Each phase of the process is carefully timed and orchestrated. Tons of coke, pig iron, scrap, and other raw materials must arrive at the appropriate machinery exactly when needed, blast furnaces must be stoked to temperatures of at least 1450 degrees Celsius, and the steel must be cast before it has time to cool. In the making of pig iron, the stages of the process can be handled through linear production, but in the steel plant, logistics and customer requirements add complexity.
To maximize throughput while meeting these operating constraints, HKM engineers developed an automated scheduling system in MATLAB®. “MATLAB enabled us to rapidly develop a system for global optimization of our steel process, deploy it as a Java component in our production environment, and run it as a computing cluster,” says Alexey Nagaytsev, project manager at HKM. “With MATLAB we can easily make changes to incorporate new constraints and scale the system to meet new demands.”