Twin screw granulation (TSG) is increasingly used to produce granules in various industries, such as food, pharmaceutical, and fine chemicals. However, there is a large parametric space in terms of screw designs, formulation properties and operating conditions, so how to maximise the production throughput while maintaining consistent product quality is not a trivial task and still needs further investigation. In this study, the TSG process was systematically analysed using a discrete element method (DEM) based on the graphics processor unit (GPU) architectures that can provide not only macroscopic information but also microscopic insights into the complicated TSG process. In particular, the particle flow profiles and residence time distributions were obtained from the simulations and analysed in details. The effects of particle size and screw speed on flow behaviour of particles in TSG were also explored. It was shown that the mean residence time and its variance in the granulator decreased with increasing particle size and screw speed. The E-curves of the residence time with larger particle size at higher screw speed had a narrower spread, implying that particles with a larger size had similar residence time in the twin screw granulator. In addition, the cumulative distribution function, the F-curves, showed a higher increasing rate for larger particles and higher screw speeds, indicating a faster conveying efficiency. (C) 2020 Elsevier B.V. All rights reserved.