Robust Design Optimization

Variability, uncertainty and tolerance have to be incorporated to design process of technical systems to assure the highly required quality and reliability. There is a class of variability and uncertainty, which is caused by environment influences (temperature, humidity, day light etc.), load variation (force, moment), human error etc.. They are uncontrollable, unpredictable and cause the uncertainty satisfaction of the required product functionalities. The design goal is assuring of all product specifications in spite of unavoidable variability and uncertainty.

Winning customers and saving the image, great efforts are done in the industry with extremely high effort and cost. Design of experiment with many prototypes is performed. Cost-intensive product changing during pre-series-production, even in the series-production are frequently the case. The new, innovative and cost-effective approach solving this problem is robust designing product parameters in the early design process. Thereby, optimal product parameters should be found. Within, the system behavior is robust in spite of unavoidable variability. E.g. the consistent variability und uncertainty leads only to the most small variability of the product properties. So, the required product specifications will be always satisfied in spite of variability and uncertainty. This process is so-called robust design optimization. There are different optimization classes:

Maximize the reliability being minimized the failure probability of output distribution.
Maximize the quality being minimized the variance of the output distribbutions.
Maximize the product advantage being minimized the mean of the output distributions.
Minimizing the manufacturing cost being maximized the tolerances.

The great challenge of the robust design optimization is the long computing time of large deterministic product models. The optimization faces the technical feasibility and it is possible only for small product models. OptiY is the world-fastest universal robust design optization system. It allows a fast optimization with considerably few number of model calculations. Therefore, robust design optimization is also feasible for large product models.

Robust design optimization is also called design for six sigma (DFSS). It deals with an effective quality improvement tool: reduce variability and increase quality. The effort is concentrated to reduce the development cost and to improve the product quality.

Robust Design Optimization

Case Studies