The Campus 2030+ initiative at Endress+Hauser SE+Co. KG, a strategic investment program aimed at modernizing production and logistics infrastructure, forms the practical motivation for this thesis. In increasingly dynamic and data-driven manufacturing environments, internal logistics systems must support flexible planning, transparency and tighter integration with production processes. Traditional material-flow simulation approaches, however, often rely on static models and fragmented data sources, limiting their suitability for iterative planning and decision support.