Manufacturing process simulations of additive processes such as laser powder bed fusion (LPBF) can reduce trial-and-error experimentation and accelerate product development times by providing greater confidence in the shape, tolerance and quality of the as-built or post-processed part. Owing to the geometric complexity that LPBF enables, parts can oftentimes be comprised of complex, topology-optimised geometries and can contain thin walls or thin struts. These geometric features are often susceptible to distortion and buckling as a consequence of the build-up of heat and shrinkage stresses that arise from the layer-by-layer nature of the LPBF process. To overcome these challenges, simulations of the process are sought to enable engineers to design against distortion and avoid buckling. Recent years have seen a proliferation of modelling strategies, simulation tools, and software products to address these manufacturing challenges. At the same time, robust validation of the different analysis techniques with a number of geometries and with different materials has lagged somewhat behind, notwithstanding, the recent NIST Additive Manufacturing (AM) Bench exercises. In light of the wide range of predictions that were obtained by modelling the same scenarios, these benchmark studies demonstrated the strong need for greater validation data and benchmark cases to be available in the public domain. To that end, the Metal Additive Manufacturing Focus Group of the NAFEMS Manufacturing Process Simulations Working Group has been collecting benchmark data to support this industry need. This presentation comprises two case studies: one related to distortion compensation of an impeller that accounts not only for the manufacturing process but also the post-process machining, and one related to the buckling-susceptibility of a thin-walled structure built with different materials. Within these case studies, different modelling and simulation strategies are explored; reference to similar studies undertaken in published literature are highlighted; and the key differences between designing against distortion, which can be compensated for, and buckling, which cannot readily be compensated for by changing pre-adjusting the geometry in CAD, are investigated. The aim is to provide quality benchmark data and an overview of the modelling challenges related to AM that link to the Working Group’s recently published “How to” guide on modelling AM processes and future work on a “How to” guide for process chaining in AM simulations.