Investigation of remelting and preheating in SLM of 18Ni300 maraging steel as corrective and preventive measures for porosity reduction

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Abstract

One of the most critical defects in selective laser melting (SLM) is the porosity formation. Optimization of process parameters for reducing the porosity levels to lower than <1% is possible in most of the cases. Susceptibility to porosity formation can be higher for different alloys as function of chemical composition due to higher spark generation and molten pool instabilities. On the other hand, the probability of porosity formation increases in larger components due to an extended processing time. Powder recoater wear, increase in thermal load, and accumulation of particles in the processing chamber become more relevant as the processing time increases. Hence, the use of integrated monitoring and correction strategies becomes crucially important.

In this work, three different correction strategies are discussed for the correction of porosity during the SLM of 18Ni300 maraging steel. The main aim is to develop a possible correction and prevention scheme to be used within a fully monitored SLM process. The 18Ni300 maraging steel is susceptible to high levels of porosity due to the empirically observed melt-pool instabilities as well as high spark and vapor generation. The correction methods consisted of remelting of the defected layer employing different scan strategies namely “double pass,” “soft melting,” and “polishing.” As a preventive strategy, preheating at 170 °C was also evaluated. At an initial stage, all the strategies were tested throughout the part built in order to assess their general capacity in improving the part density. Surface roughness, geometrical error, and material microhardness were also evaluated to assess the impact of the strategies on the other quality aspects. The results indicate the capacity of improving the part density and reduce the part roughness effectively.

Keywords

Additive manufacturing Porosity Defect correction Defect prevention Surface roughness Geometrical error Microhardness 

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© Springer-Verlag London Ltd. 2017

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringPolitecnico di MilanoMilanItaly

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