In addition to modeling according to a systematic approach, methodical modeling includes validation, conducting simulation according to a predefined plan, and analyzing simulation results. The results can be used to gain insights into the system's behavior, identify trends, make optimizations, or decisions. Various statistical methods are applied to evaluate and improve the quality and accuracy of models, including sensitivity analysis, uncertainty analysis, and model calibration. 

Through these comprehensive analyses and in-depth evaluation of measurement data, XRG is able to perform model-based optimizations.This includes calculating optimal system performance and using specially developed data-based surrogate models. These surrogate models are used to efficiently represent complex systems and enable global optimization even with large and complex system models. By combining precise measurement data, thorough analysis, and advanced optimization techniques, XRG provides solutions designed to maximize system performance and efficiency.