Modeling, observer design, and control of continuous slab reheating furnaces

In the steel industry, products are reheated in continuous reheating furnaces as a preparation for rolling. The reheating process requires large amounts of energy and incurs high costs. The temperature during this process is decisive for the product quality. Based on mathematical process models, state observers and controllers for the non-measureable product temperature are developed. The nonlinear model-predictive multi-input multi-output controller ensures a high accuracy, minimized energy consumption, and reduced CO2-emissions of the reheating process. Read more →

Thermal model and optimal time scheduling of hot rolling

In a heavy-plate rolling mill, hot slabs are rolled out. The plate temperature depends significantly on the process times and it directly influences the product quality. Mathematical models are used for better prediction and control of the product temperature. These models are also useful for an optimization of the processing times. Read more →

Optimization of process times and product sequences in a hot-rolling mill with batch-type reheating furnaces

In semiconductor manufacturing, sputtering processes require targets made of pure metals or alloys. The hot-rolling plant considered in this project produces such target of sintered refractory metal slabs. The goals of this project are to minimize the reheating times and to optimize the product sequence and the processing times for maximum product throughput. Read more →

Automated Handling of Highly Deformable Materials

In this project, a prototype of a handling system is set up and the potential of modern model-based control to handle limp materials is examined. The concepts are applicable to many other issues, such as the automated lamination of large vinyl sheets, textile handling, etc. Read more →