Understanding and predicting the diverse material properties and behaviours exhibited by additively manufactured (AM) components across different length scales remains a major challenge. Addressing this, we have developed a suite of multiscale material models suitable for AM parts, enabling the capture of key features from melt pool formation through to the mechanical response at the component scale. The developed framework includes melt-pool-scale thermal simulations using the finite difference method, microstructure evolution modelling via cellular automata [1], and micromechanical simulations based on crystal plasticity finite elements. An analytical approach has also been incorporated to rapidly estimate effective elastic properties over larger volumes. All models have been validated against experimental results for alloys fabricated predominantly by laser powder bed fusion, with some extension to directed energy deposition. Through the use of advanced computational tools, we explore the complex interplay between AM process parameters, evolving material microstructure, and resultant component performance. Particular emphasis is placed on how variations in processing conditions influence microstructural features and mechanical behaviour. High-performance computing resources are employed to enhance the efficiency of process-structure simulations. By optimising cellular automata algorithms, we successfully simulated grain structure evolution in a part exceeding 1,000 mm³ in volume on a workstation [2]. This integrative multiscale modelling approach not only deepens our understanding of AM process-structure-property relationships but also supports more efficient and predictive materials engineering for AM applications, helping overcome key barriers to wider industrial adoption. REFERENCES [1] Zinovieva, O., Zinoviev, A., Romanova, V., & Balokhonov, R. Three-dimensional analysis of grain structure and texture of additively manufactured 316L austenitic stainless steel. Additive Manufacturing (2020) 36, 101521. http://dx.doi.org/10.1016/j.addma.2020.101521 [2] Zinovieva, O., Zinoviev, A., Gokcekaya, O., & Tang, Y. Large-scale microstructure modelling of an additively manufactured part using cellular automata. IOP Conference Series: Materials Science and Engineering (2024) Vol. 1310, No. 1, p. 012005. http://dx.doi.org/10.1088/1757-899x/1310/1/012005