Today, manufacturers do not fully leverage the potential of Computer Aided Engineering (CAE) for the design of machine tools and production machines. Common design tools for drive systems and other machine components build on an algebraic system description. However, dynamic quality criteria that have a significant impact on the achievable accuracy and productivity cannot be evaluated with purely algebraic descriptions. Generally, dynamic criteria can be incorporated in signal-oriented models from control engineering, but the modeling process is time-consuming, knowledge-intensive and the reusability of models is limited. This paper presents a methodology to simplify the optimization of machine components, such as feed drives, while taking dynamic quality criteria into account. The method is based on the object- and component-oriented modeling language Modelica. For the quick development of models with limited expert-knowledge the models are integrated in an extensible model library. Modern mathematical optimization methods support the systematic search for a combination of system components and parameters with regards to the defined quality criteria. Therefore different design alternatives can quickly be analyzed and compared.
Özdemir, D., Herfs, W., & Brecher, C. (2016). Approaching the Dilemma between Plan and Value in Computer Aided Engineering of Production Machines. In Procedia CIRP (Vol. 41, pp. 141–146). Elsevier B.V. https://doi.org/10.1016/j.procir.2016.01.017