Multi-axis tool path optimization and deposition modeling for cold spray additive manufacturing AITranslate

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DOI：https://doi.org/10.1016/j.addma.2020.101779

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In this study, a 3D deposition model is developed for cold spray additive manufacturing that utilizes sequential layers and a Gaussian-shaped deposition profile. The model is designed to be computationally efficient to compute for changes to the tool-path velocity. A gradient-descent-based tool path optimization algorithm is proposed to enable manufacture of arbitrary convex deposit shapes. The algorithm works by correcting the tool-path velocity to compensate for local thickness deviations due to part geometry. The combined model and optimization algorithm take STL files of the initial tool surface and targeted deposit surface as input and generate robotic g-code of the optimized tool path for a 6-axis robotic arm as output. The model is calibrated by experiments that include line sprays and particle velocimetry measurements. The path optimization scheme is evaluated by experimental test coupons in which a thick cold spray deposit is applied to a convex surface with a 0.5 mm radius of curvature.