Qualification assessment of high-value component remanufacturing and repair via simulation-based tools

Abstract

Directed Energy Deposition (DED) is increasingly used for the remanufacturing and repair of high-value metallic components, where qualification is often limited by the impracticality of destructive testing and extensive experimental campaigns. In this context, high-fidelity numerical simulations play a critical role in enabling predictive assessment of thermal, mechanical, and solidification phenomena relevant to component integrity. This work investigates the influence of laser power strategies on process stability, thermo-mechanical response, and solidification-driven quality in DED remanufacturing. A conventional constant-power strategy is compared with a modulated-power approach designed to mitigate heat accumulation and stabilize melt-pool behavior. A coupled thermo-mechanical simulation framework based on an embedded-domain formulation is employed, allowing automated handling of complex repair geometries on background meshes. The model captures transient heat transfer, temperature-dependent elasto-viscoplasticity, material deformation, melt-pool morphology, distortion, residual stresses, and solidification-based quality indicators derived from the thermal field. The results show that power modulation substantially improves process stability by maintaining nearly constant melt-pool penetration, area, and volume throughout deposition. Compared with constant power, modulation reduces global warpage and narrows the displacement distribution, while locally increasing residual stresses near the substrate–deposit interface due to enhanced mechanical constraint. Qualification indicators reveal reduced cumulative time above melting, increased cooling rates, and higher thermal gradients under modulated power, indicating more favorable solidification conditions. In contrast, the Niyama criterion shows limited sensitivity among strategies. These findings demonstrate that simulation-driven power modulation enhances geometric accuracy, process stability, and solidification quality in DED remanufacturing. The proposed numerical framework provides a robust, non-destructive basis for qualifying high-value repaired components, supporting informed process optimization where experimental qualification is constrained.