Powder bed fusion–laser beam (PBF-LB) additive manufacturing enables the production of intricate, lightweight metal components aligned with Industry 4.0 and sustainable principles. However, residual stresses and distortions challenge the dimensional accuracy and reliability of parts. Inherent strain methods (ISMs) provide a computationally efficient approach to predicting these issues but often overlook transient thermal histories, limiting their accuracy. This paper introduces an enhanced inherent strain method (EISM) for PBF-LB, integrating macro-scale temperature histories into the inherent strain framework. By incorporating temperature-dependent adjustments to the precomputed inherent strain tensor, EISM improves the prediction of residual stresses and distortions, addressing the limitations of the original ISM. Validation was conducted on two Ti-6Al-4V geometries—a non-symmetric bridge and a complex structure (steady blowing actuator)—through comparisons with experimental measurements of temperature, distortion, and residual stress. Results demonstrate improved accuracy, particularly in capturing localized thermal and mechanical effects. Sensitivity analyses emphasize the need for adaptive layer lumping and mesh refinement in regions with abrupt stiffness changes, such as shrink lines. While EISM slightly increases computational cost, it remains feasible for industrial-scale applications. This work bridges the gap between simplified inherent strain models and high-fidelity simulations, offering a robust tool for simulation-driven optimisation.

Powder Bed Fusion–Laser Beam (PBF-LB) is a leading technique in metal additive manufacturing, yet it continues to face challenges related to residual stresses and distortions. The inherent strain method has emerged as a valuable predictive tool, offering early assessments of part behaviour due to its simplicity and manageable computational demands. However, accurately defining the inherent strain tensor, which is critical for these models, remains a challenge. This study provides a comprehensive analysis of the local meso-scale model definition and inherent strain calculation procedure in the PBF-LB process using a multi-scale modelling approach. The primary objective is to guide the definition of local high-fidelity thermo-mechanical models. This research investigates the contributions of thermal, plastic, and activation strains (strains due to Finite Element (FE) activation) to the inherent strain tensor, demonstrating the significant impact of activation strains. A sensitivity analysis identified an optimal control volume size to ensure minimal boundary effects. An optimised local high-fidelity model is proposed to efficiently calculate inherent strain tensor, significantly reducing computational costs without compromising accuracy. The method was validated by applying it to a complex SBA actuator geometry, which showed good agreement between predicted and experimental distortions. The consistency of the proposed method with empirically derived tensors further reinforces its potential to improve predictive capabilities in the PBF-LB process, ultimately enhancing part quality.

(English) Metal additive manufacturing (MAM), particularly powder bed fusion using a laser beam (PBF-LB), has transformed manufacturing by enabling the production of intricate and optimised metal components directly from digital designs. This process offers major advantages such as material efficiency, high geometric flexibility, and the ability to produce lightweight, customised parts. However, its industrial adoption is hindered by challenges such as large residual stresses and distortions resulting from steep temperature gradients and rapid thermal cycles inherent in layer-by-layer manufacturing process. These issues compromise dimensional accuracy and structural integrity, posing barriers to the broader implementation of the technology. High-fidelity thermo-mechanical finite element (FE) simulations can predict these phenomena but their high computational cost makes them impractical for large-scale industrial applications. The inherent strain method (ISM) has emerged as an efficient alternative, condensing complex thermal and mechanical phenomena into an inherent strain tensor applied in simplified elastic simulations. While ISM significantly reduces computational time, conventional implementations often lack robustness, requiring extensive recalibration for different geometries and scanning strategies and failing to capture spatial and temporal variations in thermal histories. This thesis addresses these limitations by developing an enhanced inherent strain method (EISM) for powder bed fusion (PBF), improving ISM's predictive accuracy and extending its applicability to complex industrial geometries. By integrating a macro-scale thermal analysis into ISM, the method dynamically refines the precomputed inherent strain tensor based on part-scale temperature evolution. This enhancement better accounts for geometry- and boundary-specific thermal effects, improving distortion predictions compared to conventional ISM. Additionally, this work tackles the fundamental challenge of determining inherent strain tensors necessary for ISM-based methodologies. Two complementary approaches are proposed: (1) an empirical calibration strategy using twin-cantilever beam coupons, where distortions measured after partial cutting are used to determine best-fit inherent strain tensors via inverse engineering, and (2) a numerical approach employing a meso-scale thermo-mechanical model within a multi-scale framework, computing local inherent strains and homogenising them to obtain macro-scale inherent strain tensors. Comprehensive experimental calibration and validation were conducted using Ti-6Al-4V components manufactured via PBF-LB. Temperature histories were recorded with embedded thermocouples, while distortion and residual stress data were acquired using coordinate measuring machines (CMM), 3D scanning, and incremental hole-drilling, respectively. The empirical and numerical methodologies for inherent strain tensor determination, along with EISM, were validated across multiple geometries, including twin-cantilever beams, a non-symmetric bridge, and an industrial aerospace component (the Steady Blowing Actuator). The results demonstrated that EISM significantly improved distortion predictions while maintaining computational efficiency, reducing errors by more than half compared to conventional ISM. In conclusion, this thesis presents two methods for calculating the inherent strain tensor (empirical and numerical) and introduces the EISM methodology for distortion prediction, improving the accuracy of distortion prediction in PBF-LB. In this way, the dependence on trial-and-error-based experimental testing is reduced, moving towards an optimised simulation-based design and facilitating the industrial adoption of MAM. (Català) La fabricació additiva de metalls, en particular la fusió de llit de pols mitjançant làser (\textit{PBF-LB, per les seves sigles en anglès, Powder Bed Fusion - Laser Beam}), ha revolucionat la manufactura industrial en permetre la fabricació directa de components metàl·lics complexos i optimitzats a partir de models digitals. Aquest procés ofereix diversos avantatges clau, com una major eficiència en l’ús del material, flexibilitat geomètrica i la capacitat de produir peces amb dissenys avançats. No obstant això, els ràpids cicles tèrmics inherents a la fabricació additiva capa per capa generen alts gradients tèrmics. Això dona lloc a tensions residuals i distorsions que comprometen la precisió dimensional i la integritat estructural de les peces, limitant-ne l’adopció a nivell industrial. Les simulacions termo-mecàniques basades en el mètode dels elements finits (MEF) permeten predir aquests efectes amb alta fidelitat, però el seu elevat cost computacional en restringeix l’aplicabilitat en entorns industrials. Com a alternativa, el mètode de la deformació inherent (\textit{ISM, per les seves sigles en anglès, Inherent Strain Method}) simplifica el problema en condensar els efectes termo-mecànics en un tensor de deformacions aplicable en simulacions elàstiques. No obstant això, la determinació precisa d’aquest tensor continua sent un repte, fet que afecta la fiabilitat de les seves prediccions en geometries industrials complexes. Aquesta tesi presenta un mètode millorat de deformació inherent (\textit{EISM, per les seves sigles en anglès, Enhanced Inherent Strain Method}), que millora la capacitat predictiva de l’ISM integrant una anàlisi tèrmica a escala macro amb l’ISM original. Així, el tensor de deformació inherent es modifica dinàmicament en funció de l’evolució tèrmica global de la peça. Aquesta millora permet incorporar els efectes tèrmics específics de la geometria i les condicions de contorn....