This project works out the basis for resource optimization with methods of statistical process control. Optimal conditions get defined via consistent reduction in the variation of all relevant process parameters. Additionally, new sensor systems get applied to enable process control and quality assurance in the project and provide predictive and adaptive decision support. Based on these data, statistical models of the impact of raw material composition, additives, water regime, particle structure and the compaction in production get generated. Due to the involved stakeholder (pellet producer), findings can be validated in practice in different types of industrial processes.