The SynErgie project, carried out under the sub‑project F2‑2_AEP (03SFK3F2‑2) from 1 November 2019 to 31 October 2022, focused on synchronised and energy‑adaptive production techniques that align industrial processes with fluctuating energy supplies. The core scientific effort centred on the evaluation and extension of an Energy Flexibility Data Model (EFDM). Through a series of workshops, the team identified key requirements such as data protection, absolute load curves, cost and risk assessment, forecast quality, location of service provision, and the influence of external factors. The model was subsequently expanded to incorporate dynamic variables, enabling a more realistic representation of marginal costs for flexibility services and allowing the inclusion of production risk factors identified in parallel work packages.
Parallel to the data model work, the project developed a cost‑based production control system. A prototype instance of the AEP‑Solution4 platform was installed and customised within the IGCV‑Virtual Fort Knox development environment. The team defined the overall data flow between the S4P Manufacturing Execution System (MES) and the AEP‑Solution4 interface, and established communication pathways that integrate energy supply data into production scheduling. Workshops with IGCV and S4P facilitated the quantification and modelling of cost factors, ensuring that the control system could evaluate the impact of energy flexibility measures on traditional production objectives. The demonstrator for inherent storage and bivalent consumers was realised, showcasing how embedded storage capacities and dual‑mode devices can be leveraged within the cost‑based control framework to enhance flexibility and reduce energy expenditures.
Risk assessment was addressed in a dedicated work package, where production risks associated with the deployment of flexibility services were quantified. This risk data feeds back into the EFDM, allowing operators to weigh the trade‑off between cost savings and potential disruptions. The project also produced a set of performance metrics, such as improved forecast accuracy and reduced energy costs, although specific numerical values were not disclosed in the report. Nevertheless, the integration of dynamic factors and risk considerations is expected to yield measurable gains in energy efficiency and operational resilience.
The collaborative structure of SynErgie involved several partners. IGCV and S4P provided industrial expertise and MES integration, while AEP contributed the solution platform and data modelling capabilities. The University of Applied Sciences Darmstadt (h_da) participated in knowledge transfer activities, delivering seminars to students and early‑career researchers. The consortium’s broad reach facilitated the identification of new distribution channels and market access opportunities, positioning AEP as a leading provider of holistic, energy‑oriented Industry 4.0 solutions tailored to small and medium‑sized enterprises. The project’s outcomes are slated for commercialization in 2023 and 2024, with plans to embed the developed solutions into the existing product portfolio and to offer consulting and implementation services beyond the project lifetime.
Funding for the initiative was provided through a German federal research grant, supporting the consortium’s efforts to advance sustainable manufacturing practices. The project’s results have already been disseminated through academic publications, including articles on additive manufacturing in automotive production, urban pharmaceutical production concepts, and takt time optimisation in custom manufacturing. By aligning industrial processes with renewable energy dynamics, SynErgie aims to contribute to the competitiveness and sustainability of the German manufacturing sector, while also preparing participants for forthcoming EU Corporate Sustainability Reporting requirements.