A review of Computational Modelling of Additive Layer Manufacturing - multi-scale and multi-physics

Abstract

This paper presents a review of the state-of-the-art in computational modelling of the Additive Layer Manufacturing (ALM) process, with a description and examples of models being developed at Swansea University, and a comparison to efforts from other commercial and academic organisations. As a process, ALM is strongly based on computational control and the production of net- shape parts, computational modelling is being used to understand and improve the process, as well as to create new and optimised functionality of components. Modelling efforts range from discrete element models of powder flow, to micro-and macro- scale models of the laser melt-pool, coupled thermal-structural models to predict residual stress, and automated optimisation methods for the development of new components. Modelling can also be used at a microstructural level for the prediction of the bulk properties. In all instances, the modelling is used with the purpose of increasing understanding to address known problems of the ALM process. Thus, as examples, residual stresses arise in metallic parts due to the requirement of building each layer from a base-plate with supports, and modelling can help reduce and optimise the support layout to produce as-built parts with minimal residual stress for maximum strength and minimum distortion. Understanding the heat transfer at the level of the melt-pool helps to reduce porosity and gas entrainment, as well as control the local heating rates which affect the formation of balling, which has been linked to surface roughness and also to porosity. If one looks at the evolution of computational models for casting as an indication of the way in which computation of modelling of ALM could be going, one of the long-term, but most highly coveted achievements would be a full process model, which allows the integration of micro- and macro-models of the process, with life-time component property prediction and the capability of simulating design and manufacturing iterations for a final component with optimised functionality.