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Open AccessArticle

Laser Direct Metal Deposition of 2024 Al Alloy: Trace Geometry Prediction via Machine Learning

1
Department of Industrial Engineering, University of Salerno, 84084 Fisciano (SA), Italy
2
Department of Industrial Engineering, University of Naples Federico II, 80125 Naples, Italy
3
Fraunhofer Joint Laboratory of Excellence on Advanced Production Technology (Fh-J_LEAPT UniNaples), 80125 Naples, Italy
*
Author to whom correspondence should be addressed.
Materials 2018, 11(3), 444; https://doi.org/10.3390/ma11030444
Received: 1 March 2018 / Revised: 13 March 2018 / Accepted: 18 March 2018 / Published: 19 March 2018
(This article belongs to the Section Manufacturing Processes and Systems)
Laser direct metal deposition is an advanced additive manufacturing technology suitably applicable in maintenance, repair, and overhaul of high-cost products, allowing for minimal distortion of the workpiece, reduced heat affected zones, and superior surface quality. Special interest is growing for the repair and coating of 2024 aluminum alloy parts, extensively utilized for a wide range of applications in the automotive, military, and aerospace sectors due to its excellent plasticity, corrosion resistance, electric conductivity, and strength-to-weight ratio. A critical issue in the laser direct metal deposition process is related to the geometrical parameters of the cross-section of the deposited metal trace that should be controlled to meet the part specifications. In this research, a machine learning approach based on artificial neural networks is developed to find the correlation between the laser metal deposition process parameters and the output geometrical parameters of the deposited metal trace produced by laser direct metal deposition on 5-mm-thick 2024 aluminum alloy plates. The results show that the neural network-based machine learning paradigm is able to accurately estimate the appropriate process parameters required to obtain a specified geometry for the deposited metal trace. View Full-Text
Keywords: laser direct metal deposition; aluminum alloy; machine learning; artificial neural network laser direct metal deposition; aluminum alloy; machine learning; artificial neural network
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Caiazzo, F.; Caggiano, A. Laser Direct Metal Deposition of 2024 Al Alloy: Trace Geometry Prediction via Machine Learning. Materials 2018, 11, 444.

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