Single bead geometry modelling and optimization in laser direct energy deposition

Modelling and controlling bead geometry using process parameters is an important task in additive manufacturing, as it enables the design of printing processes such that it produces 3D parts as accurate and fast as possible. In this work, bead geometry control was done using a laser wire direct energy deposition device and a pipeline was provided that includes data collection, modelling and optimization. The data collection phase explored the feasible region for process parameters, and the region was mapped using different DOEs. Then, the experimental beads were scanned with a laser scanner, and the resulting scans were analysed to produce a data set including process parameters wire feed rate, travel speed and laser power along with performance parameters bead height and width. In the modelling phase, response surface methodology and support vector regression were used to build the best possible models for bead height and width. Next, optimization scenarios were solved to control the bead geometry and the process, revealing what kind of problems can be solved using optimization. All phases were described without passing a mathematical background. The results of this work provide a clear and detailed description of each phase and aim to serve as a good example of a process that can be repeated and modified

Coaxial Wire Laser-based Additive Manufacturing of AA7075 with TiC Nanoparticles

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Industrial IoT system for laser-wire direct energy deposition: data collection and visualization of manufacturing process signals

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Using artificial neural networks to model single bead geometries processed by laser-wire direct energy deposition

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