This paper discusses the principle and the relevance of an in-situ monitoring system for Selective Laser Melting (SLM). This system enables the operator to monitor the quality of the SLM job on-line and estimate the quality of the part accordingly. The monitoring system consists of two major developments in hardware and software. The first development, essential for a suitable monitoring system, is the design of a complete optical sensor set-up. This set-up is equipped with two commercially available optical sensors connected to a FPGA which communicates directly with the machine control unit. While the sensors ensure a high quality measurement of the melt pool, the FPGA's main task is to transfer the images from the sensors into relevant values at high sample rates (above 10kHz). The second development is the data analysis system to translate and visualize measured sensor values in the format of interpretable process quality images. The visualization is mainly done by a 'Mapping algorithm', which transfers the measurements from a time-domain into a position-domain representation. Further offline experiments illustrate an excellent compatibility between the in-situ monitoring and the actual quality of the products. The resulting images coming out of this model, illustrate melt pool variations which can be linked to pores that are present in the parts.
Selective laser melting (SLM) is an additive manufacturing technique in which metal products are manufactured in a layer-by-layer manner. One of the main advantages of SLM is the large geometrical design freedom. Because of the layered build, parts with inner cavities can be produced. However, complex structures, such as downfacing areas, influence the process behavior significantly. The downfacing areas can be either horizon tal or inclined structures. The first part of this work describes the process parameter opti mization for noncomplex, upfacing structures to obtain relative densities above 99%. In the second part of this research, parameters are optimized for downfacing areas, both horizontal and inclined. The experimental results are compared to simulations of a ther mal model, which calculates the melt pool dimensions based on the material properties (such as thermal conductivity) and process parameters (such as laser power and scan speed). The simulations show a great similarity between the thermal model and the actual process.
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