Direct Laser Deposition has been considered as a method to repair and rebuild the industrial parts. Considering the possibility of the formation of structural defects due to the process parameters, assessing the selection of the optimum laser cladding parameters to minimize these defects is a crucial subject. Therefore, a model to predict the single-track geometric characteristics based on the three main process parameters namely, laser power, scanning speed and powder feed rate was presented to prevent the formation of defects in the deposition of Stellite 6 on martensitic stainless steel. Application of the linear regression method coupled with genetic optimization algorithm resulted in the optimum combined parameters (PαVβFγ), which were the basis for the generation of the process map. Eventually, based on track geometric attributes, an optimum region was introduced on the process map and to validate the capability of the prediction model, three single tracks were selected for multi-track laser deposition with a 30%, overlapping ratio concluded from derived equations. Investigation of these three multi-tracks indicated that the one with the least dilution (2.14 %) and the most wetting angle (52°), contained various defects, namely lack of fusion, delamination, and unmelted powder defect. Furthermore, the multi-track with high dilution resulted in the penetration of alloying elements from the substrate to the deposited clad and vice versa. Finally, the multi-track which was selected from the optimum region, presented the best deposited layer with no visible defects, which validated the proposed model.
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