Open Access

The importance of stainless and special steel products has increased substantially in recent decades, as their use has shifted from niche special applications to widespread popular function. Clearly, the vacuum oxygen decarburization (VOD) process plays a major role in stainless steel production. In order to achieve extremely low carbon ratios in the presence of high chromium content, oxygen is blown under reduced pressure conditions. Despite the well-known determination of the required amount of oxygen, the operation practice itself seems to vary in the field. This gives rise to the question of the existence of a consistent optimized control strategy. The present master’s thesis addresses the existing optimization problem by using a multiple-validated VOD process simulation model. As a first step, the optimization problem is defined by the examination of the existing model. Thus, the process model flow is step by step transformed into mathematical terms. Subsequently, a variable study is carried out evaluating the influences of the oxygen blowing rate, stirring gas rate and the system pressure on the result of the model. Based on the findings, an optimization algorithm is then implemented to generate enhanced control strategies with respect to the given optimization criterion: minimize chromium oxidation. Finally, the results are demonstrated by simulations and tests of generated control strategies with the existing model. These tests clearly show an improvement regarding the optimization criterion. Moreover, the results demonstrate numerically and visually, that the newly developed algorithm generates enhanced control strategies.