Optimisation of quality and energy consumption for additive layer manufacturing processes

Additive Layer Manufacturing (ALM) has great potential to be a viable automated direct manufacturing process for the aerospace, automotive and medical industries. By using layer-by-layer consolidation of raw materials to build three-dimensional near net or net shape objects, ALM enables the recycling of the non-consolidated powder materials and manufacturing of light weight parts, allowing energy and materials saving. One of the main challenges in various ALM processes is to reduce the energy required for the part building process and at the same time maintain the surface quality of the parts, affected by the "stair stepping" effect, as this has aesthetic and functional importance for industrial applications. These objectives are competing criteria and significantly influenced by the build orientation of the ALM parts. This study investigates a computational technology for the identification of optimal part orientations for the minimization of surface roughness and simultaneously energy consumption in the manufacturing process. The computational model based on a multi-objective optimization technique has been developed to predict and optimise the energy consumption and surface quality objectives. The output of the computational optimisation includes the complete set of Pareto solutions, which define the set of best compromises between the chosen objectives.