Bead Geometry Prediction in Laser-Wire Additive Manufacturing Process Using Machine Learning: Case of Study

In Laser Wire Additive Manufacturing (LWAM), the final geometry is produced using the layer-by-layer deposition (beads principle). To achieve good geometrical accuracy in the final product, proper implementation of the bead geometry is essential. For this reason, the paper focuses on this process and proposes a layer geometry (width and height) prediction model to improve deposition accuracy. More specifically, a machine learning regression algorithm is applied on several experimental data to predict the bead geometry across layers. Furthermore, a neural network-based approach was used to study the influence of different deposition parameters, namely laser power, wire-feed rate and travel speed on bead geometry. To validate the effectiveness of the proposed approach, a test split validation strategy was applied to train and validate the machine learning models. The results show a particular evolutionary trend and confirm that the process parameters have a direct influence on the bead geometry, and so, too, on the final part. Several deposition parameters have been found to obtain an accurate prediction model with low errors and good layer deposition. Finally, this study indicates that the machine learning approach can efficiently be used to predict the bead geometry and could help later in designing a proper controller in the LWAM process

New insights into the origin of fine equiaxed microstructures in additively manufactured Inconel 718

Fine equiaxed grain regions are frequently observed in additively manufactured Inconel 718 alloy. Based on a grain-to-grain orientation analysis using EBSD, many assemblies of neighboring grains in these regions have been found to display multiple-twins orientation relationships sharing common 〈110〉directions and exhibiting 5-fold symmetry. This is an experimental proof that the grain refinement observed in inconel 718 is due to Icosahedral Short-Range Order (ISRO) mediated nucleation mechanism. This is the first report of ISRO-mediated nucleation of fcc nickel which widens the perspectives on the microstructures control in additive manufacturing of Ni-based superalloys

Microstructure and mechanical properties of Ti-6Al-4V laser welds for airplane floor manufacturing application

International audienceOwing to its high strength-to-weight ratio, corrosion resistance and compatibility with carbon fibre composites, Ti-6Al-4V is a good candidate for the replacement of aluminium alloys in the manufacture of aircraft floor structure, whenever enhanced corrosion resistance is required. However forming and machining of Ti -6Al-4V is not straightforward and the cost of such an alloy makes rail manufacture from machining bars a non-viable solution. A better way to manufacture titanium alloy rails is to divide a rail into several components with fairly simple shape, which can then bejoined before limited machining to obtain the final shape. Laser welding is well suited for joining titanium alloys, as it is fast, precise and generates far less deformations than other welding processes. In this study, a 10kW fibre laser was used for joining two different grades of 5 mm thick Ti-6Al-4V plates. A comprehensive study taking into account on the laser process parameters and characteristics of both grades has been carried out to minimize distortion and to achieve sound and reproducible welds without oxide. The structure of each welded zone was examined both by optical and electron microscopy. Micro texture analyses were performed on samples before and after welding, in order to evaluate texture modifications. Differences in terms of mechanical properties, as shown by uniaxial tensile tests, were interpreted on the basis of base material initial microstructures as well as the microstructure of assemblies