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Additive Manufacturing (AM) is a class of manufacturing techniques that relies on joining material, layer-upon-layer, to create the final object. With significantly lower barriers to manufacturing-on-demand and fulfilling product variety, AM is predicted to cause a disruptive revolution in manufacturing and product-service industries. However, mainstream adoption of AM, particularly at scale, is hindered by a lack of suitable operations management understanding, exacerbating issues related to productivity and high cost. Therefore, this thesis attempts to provide a path towards efficient AM operations at scale. This is done by addressing key process efficiency concerns via operations management interventions and thus developing best practice recommendations for AM users. The methodological approach in this research is quantitative exploratory simulation of process planning in the AM system, spanning decisions at the build level-of-abstraction through to the whole production facility. Relevant metrics are developed to capture the impact of process planning on production losses and production cost, and evaluate the underlying mechanisms of efficient, effective production using the example of polymer laser sintering. The results of this work provide guidelines for AM users that centre on three overarching themes. First, production losses at the AM machine are reduced, and thus value-adding capacity is increased, by maximising the use of machine capacity in each build. Second, integrated optimisation of part allocation, packing and build scheduling leads to more cost-effective and cost-consistent AM workflows, driven by a trade-off between capacity-, failure-, and schedule adherence-related costs. Third, the implementation of manufacturing cells in AM production facilities can significantly reduce non-value-adding time in the AM workflow, at the expense of poorer flexibility in expanding the facility as the production scale increases. Overall, this thesis argues that pro