State of the Art on Robust Design Methods for Additive Manufacturing

Abstract

Additive Manufacturing (AM) technologies allow to produce functional parts with complex geometries that cannot be manufactured by conventional processes. However, the complexity of the product is increased and causes new constraints in the manufacturing process. Therefore, these new processes lead particularly to new needs in design methods. The objective of this paper is to explore and form an overall view of design methods, especially, robust design (RD) methods. Robust design is defined here as a methodology that enables to design a product with optimal performances and insensitivity to small variations of the inputs of the manufacturing process. In this contribution a state of the art of robust design methods applied to AM will be carried out.

Optimization of forming force and Erichsen index using Taguchi design of experiments: Mathematical models and experimental validation

“…The design of experiments via Taguchi method is based on a fractional factorial method. It was found that this method is widely used by researchers, for finding the effects of input factors on output parameters, 1 in various fields such as advanced manufacturing technologies 2–4 and conventional manufacturing processes. 5–10 On the first hand, the integration between this statistical method and numerical analysis was described in order to minimize the iteration number during simulation.…”