Optimization and robustness of structural product families

This thesis concerns structural optimization of product families and robustness. The overall objective is to find a method for performing structural optimization of product families subjected to multiple crash load cases and to ensure a robust behavior. A product family is a family of products where every product variant, or family member, shares at least one component with at least one other product in the family. Structural optimization of such a family is complex and for expensive function evaluations, e.g. crash simulations, the computing time to solve the problem with traditional methods gets unrealistically long. Therefore, a new optimization algorithm for product families is presented, called the critical constraint method (CCM), that reduces the number of required evaluations by only considering the active constraints in the optimal solution. Traditionally optimized structures have a tendency of being sensitive to small variations in the design or loading conditions. As these kind of variations are inevitable, it is important to account for this sensitivity in the design process to ensure the robustness of the optimized design. The thesis is divided in two parts. The first part serves as a theoretical background to the second part, the two appended articles. This first part includes introductions to the concepts of product families, optimization, meta modeling and robust design. The first appended paper presents a new optimization algorithm for product families subjected to multiple crash loads. The method is compared to traditional methods and tested on two smaller product family examples. The second paper is an application of an existing sensitivity analysis method on a large industrial application example. A sensitivity analysis is performed on a Scania truck cab subjected to an impact load in order to identify the most influencing variables on the crash responses