CAD/CAE Design Technology for Reliability and Quality

Design Optimization

Design optimization is an engineering design methodology using a mathematical formulation of a design problem to support selection of the optimal design among many alternatives. Design optimization of CAD/CAE-model parameters satisfying fully multidisciplinary and frequently various trade-off design goals as increasing speed and accuracy, minimizing temperature, noise, vibration, volume, power lost, etc... That leads to best performance and minimization of manufacturing cost. Engineers are faced with the difficult challenge of determining how to arrive at the best overall design, making the right compromises, and not sacrificing critical attributes like safety.

The design process requires frequently different disciplines. The product must be tested under several conditions to satisfy all requirements and specifications. The multidisciplinary system design optimization tool OptiY incorporates all relevant disciplines simultaneously in different CAE-fields for design verification as statics, thermal, dynamics, fluid dynamics etc… using available interfaces to external CAD/CAE-software.

CAD/CAE design workflow

After making all required CAD/CAE-models for different product modules, a system design workflow can be created in OptiY. The design process starts with defining design parameters and its value ranges. Criteria and constraints are the optimization objectives, which correlate with improvement of the product properties. After that, OptiY will choose and start the best optimization strategies to find the best parameters for these product specifications full automatically. The results can easy be transferred in CAD-system.

Curve Fitting

Curve fitting is the process of constructing a curve, or a mathematical model, that has the best fit to a series of data points. After making CAD/CAE-models, which consider sufficient all physical effects and its interactions, some model parameters have to be validated to fit the simulation curve to measurement data. It leads to an optimization problem minimizing the differences between simulation and measurement curves. A very efficient optimization strategy is available in OptiY, which bases on 1D meta-modeling technology. The curve fitting can be done extremely fast and computing-intensive dynamical simulation can be also optimized in available time.


before optimization                                                             after optimization

Case Studies