Comparative Analysis of Additive vs. Conventional Manufacturing Aluminum Alloys Properties

Thesis Abstract

In the face of growing demand for high-performance light alloys, this study examines the comparative microstructural, mechanical, and fatigue properties of aluminum alloys produced via additive manufacturing (AM) and conventional fusion and wrought processes, addressing the knowledge gap on how processing routes influence property evolution under service-like thermal and mechanical histories. The aim is to quantify differences in strength, ductility, hardness, fatigue life, and fracture behavior between AM and conventional aluminum alloys, and to establish robust predictive indicators for performance across applications in aerospace and automotive sectors. Specific objectives are to (i) characterize the microstructure and porosity content of AM (directed energy deposition and selective laser melting) versus conventional 6061-T6 and 7075-T6 alloys; (ii) compare tensile, hardness, and fatigue responses under identical heat-treatment regimes; (iii) evaluate residual stresses and corrosion resistance as functions of manufacturing route; (iv) develop multivariate predictive models linking processing parameters to property outcomes; and (v) assess life-cycle implications through a preliminary cost-performance analysis. The research adopts a mixed-methods quantitative-dominant design. The population comprises commercially available aluminum alloys processed by AM (n=60 specimens across 3 alloys and 2 AM methods) and conventional methods (n=60 specimens across the same alloy compositions and heat treatments). Purposive sampling ensures representation of relevant AM process parameters (laser power, scan strategy, and layer thickness) and conventional heat treatments (solutionizing and aging temperatures). Data collection instruments include standardized tensile testing per ASTM E8/E8M, Vickers hardness testing per ASTM E92, fatigue testing at high-cycle and low-cycle regimes per ASTM E466, scanning electron microscopy (SEM) for microstructural analysis, electron backscatter diffraction (EBSD) for grain characterization, X-ray computed tomography (XCT) for porosity quantification, and X-ray diffraction (XRD) for residual stress assessment. Mechanical data will be complemented by thermomechanical simulations to model peak-aging behavior and by corrosion testing in 3.5% NaCl solution per ASTM G59. Validity and reliability will be reinforced through calibration against reference standards and replication of 10% of measurements. Data analysis will employ descriptive statistics, inferential statistics (ANOVA/MANOVA to compare groups, post hoc tests), regression analysis to relate processing parameters to properties, and Weibull analysis for fatigue life. A theoretical framework incorporating materials science concepts (micromechanically-informed strengthening, porosity-visibility effects, and residual-stress-induced performance) and established theories of materials by design will guide interpretation. The technology acceptance lens and life-cycle thinking will inform the cost-performance dimension. Expected findings include that AM aluminum alloys exhibit finer, non-equilibrium microstructures with higher dislocation densities and distinct precipitate distributions compared with conventional alloys, resulting in higher yield strengths but variable elongations dependent on porosity levels and heat-treatment optimization. It is anticipated that AM specimens will demonstrate superior fatigue resistance in certain configurations due to refined microstructures yet may show elevated residual tensile stresses necessitating post-processing like hot isostatic pressing. Regression models are expected to reveal significant interactions between laser parameters and aging temperatures on tensile strength and fatigue life, while porosity quantified by XCT will correlate strongly with scatter in fatigue performance. The study will contribute to knowledge by providing a systematic, quantitatively supported comparison of AM and conventional aluminum alloys, clarifying how processing routes affect microstructure-property relationships and service performance, and offering predictive models that integrate process–microstructure–property linkages. The main conclusion is expected to emphasize that optimized AM processing combined with tailored post-processing can yield aluminum alloys with competitive or superior performance relative to conventional materials in targeted applications, but with distinct processing windows for ensuring reliability and life-cycle efficiency. Recommendations will include guidelines for selecting manufacturing routes based on performance requirements, recommended post-processing protocols to mitigate residual stresses and porosity, and directions for future work such as integrating machine learning models with real-time monitoring to further refine process–property predictions.