Optimizing Process Parameters in Direct Laser Metal Deposition of Ti-6Al-4V for Single-Layer Track Formation: Influence on Deposition Geometry

The growing demand for high-quality metal components has exposed the limitations of conventional manufacturing techniques. Direct Laser Metal Deposition (DLMD), a key metal additive manufacturing method, offers promising capabilities but its reliability is often compromised by dimensional inconsistencies linked to melt pool anomalies. Although prior studies have explored general process optimization, there remains a critical gap in understanding how specific parameters impact geometrical stability. Hence, this study addresses these issues by investigating the effects of process parameters specifically overlap ratio and travel speed under an oscillation scanning strategy to enhance geometrical reliability in DLMD deposits specifically for single layer track. Nine experimental runs were conducted using a Taguchi design to evaluate dimensional accuracy, focusing on absolute deviation from the target deposition height (1.5 mm) and standard deviation of deposition width (3.0 mm). Surface geometry metrics were analysed using signal-to-noise (SN) ratios and ANOVA analyses. Results reveal that travel speed significantly influences both height and width consistency, with optimal values identified at 450 mm/min and 800 mm/min, respectively. Overlap ratio also affects deposition geometry, with 70% producing the most stable outcomes across both metrics. Revised ANOVA confirms the statistical significance of travel speed, while overlap ratio exhibits a weaker but notable effect. Pareto analysis further underscores travel speed as the dominant factor governing melt pool dynamics and thermal input. The findings demonstrate that precise control of travel speed is essential for achieving consistent deposition profiles, while overlap ratio serves as a secondary tuning parameter. These insights support improved process control in DLMD, enabling enhanced dimensional accuracy and repeatability in advanced manufacturing applications.