Direct Energy Deposition (DED) is increasingly adopted for the repair and remanufacturing of high-value components, offering a sustainable alternative to full part replacement. However, the qualification of repaired parts remains challenging due to the strong coupling between thermal history, mechanical response and solidification phenomena, as well as the limited feasibility of destructive testing on industrial components. In this work, a simulation-based framework is proposed to support the qualification of DED repair/remanufacturing operations at the component scale, with particular focus on Ti-6Al-4V parts. High-fidelity coupled thermo-mechanical modelling approach is employed to predict transient heat transfer, melt-pool evolution, mechanical response and solidification-related quality indicators [1]. The framework is built on an embedded-domain formulation, enabling efficient and automated simulation of complex repair/remanufacturing geometries without remeshing. Within this setting, constant power strategies are compared against simulation-assisted power modulation schemes designed to mitigate heat accumulation and stabilize melt-pool behaviour during deposition [2]. The results show that power modulation improves process stability by maintaining nearly constant melt-pool morphology, leading to better dimensional accuracy, reduced warpage, and more uniform thermal histories, while solidification indicators suggest improved conditions for microstructural control. These benefits are accompanied by locally higher residual stresses near the substrate component interface due to stronger thermal gradients and mechanical constraint, underscoring inherent trade-offs between thermal, mechanical and metallurgical responses. Overall, the study illustrates how predictive, multi-physics simulation can serve as a non-destructive qualification tool for DED-based repair and remanufacturing of high-value components. The proposed approach supports informed decision-making for process optimization and component qualification by enabling virtual assessment of process windows, power strategies, and quality metrics, aligning with emerging industrial needs for certification-oriented modelling in additive manufacturing.