The increasing requirements on technical products represent a growing challenge for the manufacturing engineering. This challenge will be met by the development of a new manufacturing technology called sheet-bulk metal forming. For the early consideration of the full potential of sheet-bulk metal forming in a design process, a design engineer has to know the process limitations as soon as possible. Hence, the objective has to be to acquire design-relevant knowledge already in the early phases of process development and to maintain this knowledge simultaneously to the further development of the process. These are the declared aims of the self-learning engineering assistance system that will carry out the acquisition and maintenance of knowledge owing to its self-learning aspect. In this article, within an evaluation of knowledge acquisition methodologies, data mining was identified as a possibility for the realization of the self-learning aptitude. The potential of data mining was shown by its application on simulation data to acquire design-relevant knowledge.