In light of anticipated energy price increases, energy-efficient operation of industrial automation systems is crucial for manufacturing companies. Reducing energy demand during non-productive phases contributes significantly to overall efficiency. Currently, there is no comprehensive scientific framework addressing the energy-efficient operation of factory automation systems at a multi-subsystem level. Detailed instructions and strategies for interacting subsystems are essential for achieving energy savings. The proposed automaton-based system model allows for an analytical description of both structural and behavioral aspects of these systems. This mathematical modeling forms the foundation for identifying optimal strategies through a structure-exploiting procedure that facilitates efficient computation. These strategies quantify potential energy savings and assist in technical implementation. Given the complexity of computing optimal strategies, a novel approach is developed to enhance efficiency by leveraging the model's structure. Evaluations using real-world automation system models ensure the feasibility of executing strategies and allow for the assessment of design decisions. The accuracy of predictions is tested against model-to-system deviations, and economic considerations further evaluate the approach. Ultimately, the concepts and methods presented can significantly reduce energy demand in non-productive phases of
