Robust response design for heterogeneous systems based on metamodels

The robustness of the system response to production factors and operating conditions is a big challenge as the systems grow in complexity and heterogeneity. In this paper, we propose a method that solves the robust parameter design problem. First, we define some cost functions based on the distribution of the system´s response and, second, we estimate the dependence of the cost function on the controllable factors. With such dependency we are then able to determine the setting of controllable factors that yields the minimum of the cost function. By this method we reduce the number of required simulations by at least one order of magnitude. The method is applied on a beam leveling application and proved to be successful even with high number of heterogeneous factors (> 30). The method is validated by comparing the estimated cost functions with direct simulations. The estimated values differ by only 5% from the simulated ones.