In many areas of mechanical engineering, it is often a great challenge to find the optimal compromise between cost and quality standards.
While up to now, mainly single answers to a problem have been prepared and contrasted, we develop software applications that show the complete spectrum of possibilities that may be appropriate.
Our decision support tools enable the detailed analysis of separate solutions and, at the same time, consider them in the context of the total number of solutions.
At the basis of our approach is our development of appropriate models to forecast behavior. Essential in this approach is the close meshing of modeling with optimization: In most case, model hierarchies are used in which complex models verify simpler models that have been specially adapted for the optimization algorithms and allow for an efficient evaluation.