Collaborative Multidisciplinary Design Optimization : A Framework Applied on Aircraft Systems and Industrial Robots

In a product development process, it is crucial to understand and evaluate multiple and synergic aspects of systems such as performance, cost, reliability and safety. In order to improve the foundations for decision-making, this thesis presents methods that are intended to increase the engineering knowledge in the early design phases. In complex products, different systems from a multitude of engineering disciplines have to work tightly together. Collaborative design is defined as a process where a product is designed through the collective and joint efforts of domain experts. Thus, a Collaborative Multidisciplinary Design Optimization (CMDO) process is proposed in the conceptual design phase in order to increase the likelihood of more accurate decisions being taken early on. To enable higher fidelity based CMDO, it is necessary to validate the tools and models utilized. This can be done with so-called low cost demonstrators. The physical demonstrators increase the engineer’s confidence regarding the final product by validating the models as well as revealing many unknowns and thus further increasing the engineering knowledge. The performance of the presented methods is demonstrated with two industrial applications, aircraft conceptual system design and industrial robot design.