Due to their excellent strength-to-weight ratio, the use of composite materials in various industries (e.g., aviation, automotive, renewable energy systems, etc.) is constantly increasing. To keep up with the rising demand for composite components and simultaneously ensure consistent quality, automation is more and more inevitable and therefore in the spotlight of modern production strategies. Especially processes such as automated fiber placement (AFP) or tape laying (ATL), diaphragm and press forming or filament winding and are becoming increasingly established for serial production. This increase in automation, however, introduces new challenges to the development, adaptation and optimization of manufacturing processes. A key factor to efficient development and optimization is process simulation, which enables the reduction of cost- and time-expensive trial-and-error experiments and a better process understanding and process control. However, there is still a lot of research potential in the field of process simulation, for example regarding computational efficiency, detailed outcome predictions for thermoset and thermoplastic fiber reinforced composites, effects of effects as well as inclusion of the process simulations results in the structural analysis of the part . The mini symposium “Process simulation for composite manufacturing” addresses innovations in process simulation, especially regarding detailed process modelling and accurate prediction of process outcomes. It should offer the audience the opportunity to see recent advances in the simulation and validation of automated manufacturing processes. We invite contributions with focus on (but not limited to): simulation and experimental validation of manufacturing processes including e.g. draping, material deposition, curing, consolidation; flow simulation; process induced deformations and effects of effects; digital twins as well as process monitoring, machine learning and artificial intelligence in process optimization. Participants should gain insights into innovative techniques in process simulation and identify current gaps and future research directions.