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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.

S e le c tiv e L a s e r M e ltin g of C ra c k -F re e H ig h D e n s ity M 2 H igh S p e ed S te e l P arts by B a s e p la te P re h e a tin g Cracks and delamination, resulting from residual stresses, are a barrier in the world of additive manufacturing and selective laser melting (SIM) that prohibits the use of many metals in this field. By preheating the baseplate, thermal gradients are lowered and stresses can be reduced. In this work, some initial tests were performed with M2 high speed steel (HSS). The influence of preheating on density and mechanical and physical properties is investigated. The paper shows many promising results for the production of SLM parts in materials that are very sensitive to crack formation and delamination. When using a preheating of 200 °C, crack-free M2 HSS parts were produced with a relative density of 99.8%.

Owing to their attractive combination of mechanical properties, high heat conductivity and low weight, the Al–Si alloys found a large number of applications in the Additive Manufacturing field for automotive, aerospace and domestic industries. However, due to their high reflectivity and heat conductivity, they are harder to process by Selective Laser Melting. This work elaborates on both the optimisation of process parameters, in order to get nearly fully dense parts, and the material properties resulting from this specific material process combination. A process parameter window is defined, in which the formed melt pool is stable and meets the set requirements. In this process window, the parameter set for optimal density is defined. It is shown that AlSi10Mg parts produced by SLM have mechanical properties higher or at least comparable to the cast material because of the very fine microstructure.

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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.