Abstract
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.
Highlights
In recent years, additive manufacturing processes, characterized by layer upon layer construction of parts, have emerged as an alternative to conventional processes for the manufacturing of various metal materials like steel, Inconel, aluminum and titanium alloys [1,2,3,4].Due to progress in computation power and systems technology, laser-based additive manufacturing, employing a laser beam to provide thermal energy for the melting and consolidating of the additive materials, has notably advanced and is receiving a great deal of attention due to its high potential for industrial applications [1,2]
Selective laser melting (SLM) has been employed for processing various metal alloys for the biomedical, aerospace and automotive industries, being able to produce complex-shape parts in a highly efficient way and to provide properties comparable or superior to those produced by other conventional methods [3,5]
Laser direct metal deposition (DMD) is an advanced additive manufacturing technology which is attracting increasing interest due to its suitable applicability in maintenance, repair and overhaul of critical high-cost products, such as those employed in the aerospace and automotive industry
Summary
Additive manufacturing processes, characterized by layer upon layer construction of parts, have emerged as an alternative to conventional processes for the manufacturing of various metal materials like steel, Inconel, aluminum and titanium alloys [1,2,3,4]. Laser direct metal deposition (DMD) is an advanced additive manufacturing technology which is attracting increasing interest due to its suitable applicability in maintenance, repair and overhaul of critical high-cost products, such as those employed in the aerospace and automotive industry. These complex products may be subject to manufacturing-induced damages or to severe operating conditions (temperature, wear, and mechanical stresses) hindering the product’s operational. As regards the substrate materials to be processed via laser direct metal deposition, interest is growing for the repair [15] and coating [16] of 2024 aluminum alloy components This alloy is characterized by excellent plasticity, corrosion resistance, electric conductivity, and strength-to-weight ratio. According to a two-phase procedure for the estimation of the appropriate process parameters and following verification
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