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

Nault, Isaac; Ferguson, Gehn; Nardi, Aaron

doi:10.1016/j.addma.2020.101779

Cited by 14 publications

(8 citation statements)

References 17 publications

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“…As for the direct slicing, some scholars have adopted the point cloud data of a CAD model in order to layer parts. Lee et al developed a method to generate a part layer contour from three-dimensional model point cloud data, and developed an approach to simplify the number of point clouds [36][37][38]. Chen et al proposed to generate point cloud data by scanning 3D solid parts.…”

Section: Direct Slicing Algorithm Based On a Cad Modelmentioning

confidence: 99%

An Additive Manufacturing Direct Slicing Algorithm Based on a STEP Model

et al. 2022

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The Standard Template Library (STL) file is the most common data format for the description of an additive manufacturing (AM) geometric model, but it has some disadvantages, such as large errors of the geometric model description, the easy loss of topology information, data duplication, large file sizes, and so on. Aiming at these problems, a direct slicing algorithm based on a Standard for the Exchange of Product Model Data (STEP) model was proposed. For the parts composed of basic types of surfaces such as boundary curves, spherical surfaces and cylindrical surfaces, the traditional geometric method was used to calculate the intersection. For the parts with complex surfaces, the three-dimensional models were described based on Non-Uniform Rational B-Spline (NURBS) surfaces. The NURBS surfaces were layered using a discrete tracking algorithm, the tracking starting point was determined, the intersection line between the tangent plane and each NURBS sub-surface was obtained, and the closed layer contour was formed. Finally, the slicing simulations and printing experiments of solid parts were carried out using the direct slicing algorithm based on the STEP model. It was shown that the dimensional accuracy and surface quality of the printed parts from this algorithm had been significantly improved.

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Section: Direct Slicing Algorithm Based On a Cad Modelmentioning

confidence: 99%

An Additive Manufacturing Direct Slicing Algorithm Based on a STEP Model

et al. 2022

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“…Previously, geometric profile modelling in HPRAM was studied using two distinct approaches: mathematical and data-driven modelling, with the former dominating the overlapping-track profile context. In CSAM, a mathematical Gaussian superposing model is usually applied in which a single-track Gaussian function shape is assumed due to the spatial distribution of powder exiting the nozzle and numerically superposed at each trajectory location [12][13][14][15]. However, due to the complex processes involved in CSAM (and HPRAM), there is no agreement in the selection of a single mathematical function model (e.g., triangular [16,17] and trapezoidal [18] functions also used in CSAM).…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Overlapping Track Profile Modelling in Cold Spray Additive Manufacturing

Ikeuchi

Vargas-Uscategui

King

et al. 2023

International Thermal Spray Conference

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Cold spray additive manufacturing is an emerging solid-state deposition process that enables large-scale components to be manufactured at high production rates. Control over geometry is important for reducing the development and growth of defects during the 3D build process and improving the final dimensional accuracy and quality of components. To this end, a machine learning approach has recently gained interest in modelling additively manufactured geometry; however, such a data-driven modelling framework lacks the explicit consideration of a depositing surface and domain knowledge in cold spray additive manufacturing. Therefore, this study presents surface-aware data-driven modelling of an overlapping-track profile using a Gaussian Process Regression model. The proposed Gaussian Process modelling framework explicitly incorporated two relevant geometric features (i.e., surface type and polar length from the nozzle exit to the surface) and a widely adopted Gaussian superposing model as prior domain knowledge in the form of an explicit mean function. It was shown that the proposed model is able to provide better predictive performance than the Gaussian superposing model alone and purely data-driven Gaussian Process model, providing consistent overlapping-track profile predictions at all overlapping ratios. By combining accurate prediction of track geometry with toolpath planning, it is anticipated that improved geometric control and product quality can be achieved in cold spray additive manufacturing.

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“…For more complex three-dimensional loads, fibre alignment in all three directions is required. Research on multi-axis ME machines has already started to tackle the challenge [19][20][21][22][23]; they all, however, face the issue of requiring specialised machinery and intricate path planning as well as supporting structures.…”

Section: Introductionmentioning

confidence: 99%