3D in-situ based methodology for optimizing the mechanical performance of selective laser melted aluminium alloys

增材制造（AM），也称为3D打印，是一个常用术语，用于描述通过连续的材料层制造三维（3D）物体的技术。英国一直处于全球AM创新的前沿，并已建立了该技术商业化的应用程序。虽然增材制造已被普遍用于生产原型和模具几十年来，英国制造业最近一直在革命性地使用这种技术的最终用途产品在各个关键部门，由于其经济和技术效益相比，传统的制造技术。一旦目前采用AM的障碍（即，选择性激光熔化（Selective Laser Melting，SLM）是最有前途的金属增材制造方法之一，通过使用高能激光束熔化预沉积的金属粉末来制造3D部件。可持续土地管理的使用在联合王国的一些工业部门（即，航空航天、汽车、医疗、石油天然气、船舶和国防等）这是由于其能够从CAD模型生产接近最终形状的复杂部件，并因此提供稳健的设计灵活性，而不受需要一系列制造过程、更多材料消耗、更高成本和能量的传统制造方法的限制。对于以快速制造产品和进入更广泛的买方市场为目标的制造业来说，如果已经建立了工艺参数之间的相互关系及其对结构完整性和性能的最终影响，SLM似乎是他们业务的理想途径。SLM主要用于构建一系列金属材料，包括不锈钢，钛，镍和铝合金。与其他合金不同，通过SLM制造铝合金涉及更多的复杂性，这是由于它们的高反射率和热导率，这有助于刺激制造部件中的孔隙率。因此，目前缺乏了解SLM工艺参数对铝合金微观结构和材料性能的影响。确定这种未知的关系是一个非常重要的工程使命，目前代表了SLM处理的铝合金广泛使用的主要障碍。这个第一批建议的总体目标是开发一个强大的方法，优化铝合金部件的制造使用选择性激光熔化。在实现这一目标，结合使用X射线微计算机断层扫描与原位微拉伸测试阶段（允许观察的3D原位变形）将被用来调查孔隙率，材料性能和故障行为的过程参数的影响。此外，将开发基于实验的多孔塑性有限元模型，以了解孔隙尺寸和形状对变形行为的影响。

Additive Manufacturing (AM), also known as 3D printing, is a common term used to describe the technology in which three-dimensional (3D) objects are fabricated by successive layers of material. The UK has been at the forefront of global innovation in AM and has also set up applications for commercialisation of this technology. While AM has been commonly employed for producing prototypes and tooling for decades, UK manufacturing industry has more recently been making revolution by using this technology for end-use products in various key sectors due to its economic and technical benefits in comparison with traditional manufacturing techniques. Once the current barrier to adoption of AM (i.e., quality, uncertainty of the final component and expertise) has been addressed, it is expected that this new emerging time-efficient AM technology has obvious capability to considerably boost UK economic production.Selective laser melting (SLM) is one of the most promising metal AM methods where 3D components are fabricated by using a high-energy laser beam to fuse the pre-deposited metal powder. The use of SLM has been progressively increasing in a number of UK industrial sectors (i.e., aerospace, automotive, medical, oil & gas, marine and defence etc.) owing to its capability to produce near-net shape complex components from a CAD model and hence offering robust design flexibility without the constraints of conventional manufacturing methods that require a series of manufacturing processes, more material consumption, higher cost and energy. For manufacturing industry that targets to fabricate their products rapidly and access to wider purchaser markets, SLM appears to be an ideal route for their businesses if the inter-related relationships between process parameters and their ultimate effect on the structural integrity and performance has been established.SLM is prevalently used to build in a range of metallic materials including stainless steel, titanium, nickel and aluminium alloys. Unlike the other alloys, manufacturing aluminium alloys by SLM involves more complexities due to being their high reflectivity and thermal conductivity which contribute to stimulate porosity in manufactured parts. Hence, there is presently a lack of understanding about the effect of SLM process parameters on microstructure and material performance in aluminium alloys. Determining such unknown relationships are an essentially important engineering mission that presently represents a major barrier to widespread usage of SLM processed aluminium alloys.The overall aim of this First Grant proposal is to develop a robust methodology to optimize the manufacture of aluminium alloy components using selective laser melting. In achieving this, the combined use of X-ray microcomputed tomography with an in-situ microtensile testing stage (allowing observations of the 3D in-situ deformation) will be employed to investigate the impact of process parameters on porosity, material properties and failure behaviour. In addition, an experimentally based porous plasticity finite element model will be developed to understand the effect of void size and shape on deformation behaviour.