Multidisciplinary design optimization in design for additive manufacturing

ABSTRACT Design for additive manufacturing (AM) involves decision making in various design domains, including product design, material selection, and process planning. In practice, engineers typically adopt a sequential to optimize these domains consecutive order. However, coupling factors, e.g. shared variables, related constraints, conflicting objectives, are not sufficiently considered within the process, resulting an inefficient workflow suboptimal solutions. To address above issues, this paper proposes multidisciplinary optimization framework simultaneously different which enables rapid exploration complete exploitation of AM space under complex constraints. More specifically, proposed is based on concurrent method, coordinates by allowing automated exchange information. Also, utilizes surrogate modeling approach approximate high-fidelity simulations facilitating iterative process. The effectiveness validated with two examples, plate hole hook involve multiple objectives from both structure i.e. print time, area, strain energy, maximum von Mises stress.