The design of critical components for aircrafts, cars or any other kind of machinery today is typically subject to two conflicting objectives, namely the maximisation of strength and the minimisation of weight. The conflicting nature of these two objectives makes it impossible to obtain a design that is optimal for both. The most common approach aiming for a single objective optimisation problem in aerospace is to maintain the weight minimisation as the objective, whilst setting strength requirements as constraints to be satisfied. However, manufacturing methods incorporate additional restrictions for an optimal design to be considered feasible, even when satisfying all constraints in the formulation of the optimisation problem. In this context, Additive Layer Manufacturing adds remarkably higher flexibility to the manufacturability of shape designs when compared with traditional processes. It is fair to note, however, that there are still some restrictions such as the infeasibility of building unsupported layers forming angles smaller than 45 degrees with respect to the underlying one. Nowadays, it is common practice to use a set of software tools to deal with these kinds of problems, namely Computer Aided Design (CAD), Finite Element Analysis (FEA), and optimisation packages. The adequate use of these tools results in an increase in efficiency and quality of the final product. In this paper, a case study was undertaken consisting of a turbine bracket from a General Electric challenge. A computational methodology is used, which consists of a topology optimisation considering an isotropic material at first instance, followed by the manual refinement of the resulting shape taking into account the manufacturability requirements. To this end, we used SolidWorks 2013 for the CAD, Ansys Workbench 14.0 for the FEA, and HyperWorks 11 for the topology optimisation. A future methodology will incorporate the automation of the shape optimisation stage, and perhaps the inclusion of the manufacturability restriction within the optimisation formulation
