Purpose The purpose of this paper is to report on the developments in manufacturing soft magnetic materials using laser powder bed fusion (L-PBF). Design/methodology/approach Ternary soft magnetic Fe-49Co-2V powder was produced by gas atomization and used in an L-PBF machine to produce samples for material characterization. The L-PBF process parameters were optimized for the material, using a design of experiments approach. The printed samples were exposed to different heat treatment cycles to improve the magnetic properties. The magnetic properties were measured with quasi-static direct current and alternating current measurements at different frequencies and magnetic flux densities. The mechanical properties were characterized with tensile tests. Electrical resistivity of the material was measured. Findings The optimized L-PBF process parameters resulted in very low porosity. The magnetic properties improved greatly after the heat treatments because of changes in microstructure. Based on the quasi-static DC measurement results, one of the heat treatment cycles led to magnetic saturation, permeability and coercivity values comparable to a commercial Fe-Co-V alloy. The other heat treatments resulted in abnormal grain growth and poor magnetic performance. The AC measurement results showed that the magnetic losses were relatively high in the samples owing to formation of eddy currents. Research limitations/implications The influence of L-PBF process parameters on the microstructure was not investigated; hence, understanding the relationship between process parameters, heat treatments and magnetic properties would require more research. Originality/value The relationship between microstructure, chemical composition, heat treatments, resistivity and magnetic/mechanical properties of L-PBF processed Fe-Co-V alloy has not been reported previously.

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After its recent improvements described here, open source finite element software Elmer is shown to be a highly efficient option for electrical machine modeling. The parallelization of computational burden is shown to be a necessity. The methods implemented enable applying fully parallel computation to electrical machine models, including rotation and electrical circuits. Computational experiments performed demonstrate that Elmer can effectively utilize several hundreds of computational cores in parallel, making it an attractive alternative when computational speed is of high importance.