Dominik Leherbauer

The transition to sustainable energy sources presents significant challenges for energy distribution and consumption systems. Specifically, the intermittent availability of renewable energy sources and the decreasing usage of fossil fuels pose challenges to energy flexibility and efficiency. An approach to tackle these challenges is demand-side management, aiming to adapt energy consumption and demand. A key requirement for demand-side management is the traceability of the energy flow among individual energy consumers. In recent years, advancements in industrial information and communication technology have provided additional potential for data acquisition. Complementary to acquired data, a physics-based modeling and analysis approach is proposed, which describes the energy consumption with physical parameters. This results in comprehensive options for monitoring actual energy consumption and planning future energy demand supporting energy efficiency and demand-response goals. To validate the proposed approach, a case study with a 3D printer covering approximately 110 h of active printing time is conducted. The medium-term study results indicate a consistent parameter trend over time, suggesting its conceptual suitability for industrial application. The approach helps to monitor energy efficiency among manufacturing assets by identifying peak loads and consumption hotspots, and provides parameters to estimate energy consumption of manufacturing processes. Results indicate up to 50% energy savings when switching the printing material and indicate further potentials.

Optimizing and predicting the energy consumption of industrial manufacturing can increase its cost efficiency. The interaction of different aspects and components is necessary. An overarching framework is currently still missing, and establishing such is the central research approach in this paper.This paper provides an overview of the current demands on the manufacturing industry from the perspective of digitalization and sustainability. On the basisof the developed fundamentals and parameters, a superordinate framework is proposed that allows the modelling and simulation of energy-specific properties on several product and process levels. A detailed description of the individual methods concludes this work and demonstrates their application potential in anindustrial context. As a result, this integrated conceptual framework offers the possibility of optimizing the production system, in relation to different energy flexibility criteria.

Volatility in the availability of energy resources is a key challenge to master in the transition to sustainable energy sources. Especially with a rising share of renewable energy sources the situation is expected to intensify. To leverage the situation within an industrial context, energy-aware scheduling could be used. However, state-of-the-art simulation techniques use state-based energy determination, which is merely suitable for recurring manufacturing of products. In order to enable energy-aware scheduling within a changeable manufacturing environment, an alternative approach is researched. The approach aims to disaggregate the used manufacturing entities and identify the individual load patterns. Based on the individual load patterns , a simulation and optimization architecture was derived to conduct energy-aware scheduling in future applications. The used methods include the analysis of current methods for scheduling and energy consumption prediction and derivation of the component-based simulation approach based on the state-of-the-art. Depending on the inclusion of environmental dependencies two optimization architectures were created. A case study with a small-scale demonstrator was conducted to present and validate the approach. Within the scope of the small-scale demonstrator the approach could be validated. The main contribution of the publication is the provision of an approach for scheduling orders for merely non-recurring jobs.

International agreements target a reduction in greenhouse gas emissions. A major contributor to these greenhouse gas emissions is the generation and consumption of energy. By a varying supply and demand of different energy sources including renewables a varying energy mix results. A difficulty poses the determination of CO2 equivalent emissions for volatile energy types, because different energy sources have type-specific emission amounts. Within the manufacturing environment, the challenge is to allocate the resulting energy flows, respectively emission flows through the existing hierarchical structure.

The implementation of Product-Service Systems gained importance over the last years with rising competition and the need of a better fulfilment of the customers’ demands. However, whilst there are dozens of examples of products, which were transitioned to a Product-Service System, the transition from services is currently uncommon. This paper shows how an established service can be transitioned to a Product-Service System. Through the analysis of different possible solutions, the paper demonstrates how an effective conceptual design can be conducted and shows a possible way for the implementation with an existing service. The functional validation of the results shows that the approach can unleash new potentials for service providers under the right circumstances.