Determination of selective laser melting process parameters of tungsten carbide powders coated with nickel via electroless plating for improved interface properties

Tungsten carbide powders are commonly used at various industrial applications due to their high hardness. However, these powders may exhibit low binding and processing challenges without a binder. Therefore, various binding methods such as electroless Ni coating are used to hold WC powders together, increase their processability and improve the mechanical properties of the final product. Electroless Ni plating plays an important role in the use of WC powders, especially in processes such as selective laser melting. The structural, tribological, and mechanical properties of parts manufactured by SLM method are significantly influenced by the parameters employed in the process. Hence, optimizing process variables is essential to unlock the full potential of this advanced manufacturing technique. The main objective of this study was to identify the optimum process parameters for the SLM method of WC-Ni composite powders, which were prepared by coating WC powder materials with electroless Ni. Experimental investigations focused on analyzing the laser power, scanning speed, and hatch spacing parameters. The effects of these parameters on the mechanical and tribological properties of WCNi composite material were investigated using microhardness tester, tribometer device, optical microscope, 3D optical profilometer and scanning electron microscope. Eventually, it was determined that the manufacturing parameters employed in the SLM method had a significant impact on relative density, microstructure, surface roughness, hardness, and tribological properties. Samples exhibited a relative density of nearly 99%, and the highest observed hardness value was 1962 HV. This article supports a specialized SLM manufacturing process developed specifically to enhance durability and performance across a broad spectrum of industrial applications through interface improvement and the optimization of manufacturing parameters.