Investigation on mechanical properties and process parametric optimization of cmt based wire arc additive manufactured al4043 alloy cylinder

Abstract

The Wire Arc Additive Manufacturing (WAAM) process is an newlineadvanced metal additive manufacturing technique that enables near-net-shape newlineproduction. Its key advantage is the ability to fabricate large-scale metal newlinecomponents, driven by its higher deposition rates compared to other metal newlineadditive manufacturing technologies. This research focuses on improving the newlinequality of WAAM-deposited Al4043 alloy components while minimizing the newlineneed for extensive post-processing. The Al4043 alloy is frequently chosen as newlinefiller material for joining processes due to its favourable fluidity, making it newlineparticularly suitable for producing 3D printed components. newlineThe single-layer weld bead experiments were first conducted to newlineoptimize and model the input process parameters. The single-layer weld bead newlineexperiments of this study were designed using L27 orthogonal array. A total newlineof 27 experimental runs were conducted to assess responses such as Width of newlineWeld Bead (WWB), Height of Weld Bead (HWB) and Penetration of the newlineWeld Bead (PWB) with varying levels input parameters such as Welding newlineSpeed (WS), Wire feed Speed (WFS) and Arc Length Correction (ALC). newlineThe Modern Machine Learning Algorithm is used to model and predict newlinethe single layer weld bead geometrics. The Random Forest, Ada Boost and newlineXGBoost are three machine learning models used to predict the WWB, HWB newlineand PWB. newline