Formulations for robust design and inverse robust design

Abstract

In order to apply Robust Design Optimization to problems of industrial relevance, characterized by large number of variables and high computational effort, it is important to define the best strategy to solve every kind of problem. Different approaches are here presented, including multi-objective optimization and reliability optimization, based on exploitation of Polynomial Chaos Expansion for the quantification of percentiles. In addition, Tolerance Design or Inverse Robust Design methodology is presented, as an efficient approach to reduce excessive warranty costs in manufacturing process while keeping the expected quality level, by minimizing the standard deviation of the uncertain parameters.