| Abstract |
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Additive Manufacturing (AM) is widely used in the manufacture and repair of metallic parts. The process provides a means for
components of intricate geometry to be manufactured using a laser beam with material being delivered into the laser path on the
desired substrate. Parts produced by AM commonly present poor surface quality and wide dimensional accuracy; thus, machining
processes are required to obtain optimal surface integrity. Surface properties have an enormous influence on features such as
dimensional accuracy, friction coefficient and wear, thermal and electric resistance, fatigue limit, corrosion, appearance and cost.
Hence, optimum surface integrity is crucial for the proper functionality of machined workpieces.
SuPreAM project aims at optimizing surface integrity of AMed + machined steel components to reduce manufacturing expenditures
at the steel industrial sector through the minimization of scrap and avoidance of re-processing loops. Predictive models of finishing
operations will be developed considering the influence of AM technology and steel grades, machining operations, strategies and
process parameters on machinability and surface properties of AMed components, enabling the identification of main variables
affecting surface integrity. Particle Finite Element Method will be developed for the first time to study of AMed machined steels and
AM parameters will be adjusted for a new quality of lean maraging steel.
Two representative case studies have been selected. In both cases, components are real in-use parts proposed for improvement with
requirements very closely related to surface quality: 1) a plastic injection mould, surface finish is crucial to ensure quality of moulded
parts and mould behaviour (thermal fatigue and wear resistance); 2) a structural component for aerospace application, which
requires fatigue resistance. Demonstrators of both case-studies will be produced and used for model validation and comparison with
conventional steels. |
