Further process understanding and prediction on selective laser melting of stainless steel 316L
2013-11-13T11:23:34Z (GMT) by
Additive Manufacturing (AM) is a group of manufacturing technologies which are capable to produce 3D solid parts by adding successive layers of material. Parts are fabricated in an additive manner, layer by layer; and the geometric data can be taken from a CAD model directly. The main revolutionary aspect of AM is the ability of quickly producing complex geometries without the need of tooling, allowing for greater design freedom. As one of AM methods, Selective Laser Melting (SLM) is a process for producing metal parts with minimal subtractive post-processing required. It relies on the generation and distribution of laser generated heat to raise the temperature of a region of a powder bed to above the melting point. Due to high energy input to enable full melting of the powder bed materials, SLM is able to build fully dense metal parts without post heat treatment and other processing. Successful fabrications of parts by SLM require a comprehensive understanding of the main process controlling parameters such as energy input, powder bed properties and build conditions, as well as the microstructure formation procedure as it can strongly affect the final mechanical properties. It is valuable to control the parts’ microstructure through controlling the process parameters to obtain acceptable mechanical properties for end-users. In the SLM process, microstructure characterisation strongly depends on the thermal history of the process. The temperature distribution in the building area can significantly influence the melting pool behaviour, solidification process and thermal mechanical properties of the parts. Therefore, it is important to have an accurate prediction of the temperature distribution history during the process. The aim of this research is to gain a better understanding of process control parameters in SLM process, and to develop a modelling methodology for the prediction of microstructure forming procedure. The research is comprised of an experiment and a finite element modelling part. Experimentation was carried out to understand the effect of each processing control parameters on the final part quality, and characterise the model inputs. Laser energy input, build conditions and powder bed properties were investigated. Samples were built and tested to gain the knowledge of the relationship between samples’ density and mechanical properties and each process control factor. Heat transfer model inputs characterisation, such as defining and measuring the material properties, input loads and boundary conditions were also carried out via experiment. For the predictive modelling of microstructure, a methodology for predicting the temperature distribution history and temperature gradient history during the SLM process has been developed. Moving heat source and states variable material properties were studied and applied to the heat transfer model for reliable prediction. Multi-layers model were established to simulate the layer by layer process principles. Microstructure was predicted by simulated melting pool behaviour and the history of three dimensional temperature distribution and temperature gradient distribution. They were validated by relevant experiment examination and measurement.