The efficiency of the simulations with the discrete element method (DEM) is significantly improved using a novel computational strategy. The new method is developed with a focus on platforms equipped with multi‐core central processing units (CPU) and general‐purpose graphics processing units (GPU). The DEM calculations are performed in parallel on the CPU and on the GPU using pre‐calculated Verlet lists with a posteriori analysis of their consistency. The operations related to the search for possible contacts are performed on the CPU, whereas the processing of interactions, and integration of motion, are executed on the GPU. Performance analysis done for various types of tasks has shown that the new method allows to significantly decrease the average computational time and to utilize available computational resources more efficiently compared to the sequential CPU–GPU execution mode. Furthermore, due to more efficient calculations, the overall energy requirement for the proposed strategy does not exceed the demand for conventional sequential CPU–GPU computations.

Porcelain tile manufacturing is an energy-intensive industry that is in dire need of increasing productivity, minimizing costs, and reducing CO₂ emissions, while keeping the product quality intact to remain competitive in today’s environment. In this contribution, alternative processing parameters for the porcelain tile production sequence were proposed based on simulation-based process optimization. Flowsheet simulations in the Dyssol framework were used to study the impact of the milling and firing process parameters on the electrical and thermal energy consumption, final product quality, and productivity of the entire processing sequence. For this purpose, a new model of gas flow consumption in the sintering stage was proposed and implemented. During optimization, the primary condition was to maintain the product quality by keeping the final open porosity of the tile within the specified industrial range. The proposed simulation methodology proved to be effective in predicting the influence of the processing parameters on the intermediate and final products of the manufacturing sequence, as well as in estimating the production costs for the Brazilian and Spanish economic conditions. This approach has shown great potential to promote digitalization and establish digital twins in ceramic tile manufacturing for further in-line process control.