Co-simulation environment for optimizing energy efficiency in production systems
Section snippets
Introduction and motivation
A planning process of a new production facility is challenged by increasing requirements on energy and resource efficiency, while simultaneously reducing time and costs in order to retain the economic competitiveness. The decisions made in the early planning phases are of crucial importance for the future performance of an industrial facility. However, the early planning phases are characterized by diverging interests and lacking information. The more advanced the planning process, the fewer
Coupled simulation approach
The interdisciplinary approach to a comprehensive energy optimization of production facilities and the cooperation of experts from different disciplines requires an initial formalization of the system structure. The resulting generic description of the system includes the system components, interfaces, dependencies and characterizing parameters, as described in detail in [3].
Sub-model: process, machine and production system
New object-oriented modeling approaches for physical systems, e.g. Modelica or Simscape, allow developing modular and easily extensible models employing reusable model classes of structural components. The underlying acausal model description based on energy flows offers the possibility to create multi-domain models combining, e.g. electrical, mechanical as well as thermal aspects of machine tools [6]. Fig. 4 shows an exemplary object-oriented system model of a drive train in a turning lathe.
Industrial case study
A case study was carried out using the co-simulation within the planning process of a metal cutting company performing small batch production, which moves the production to a new building, mainly keeping the existing production equipment. The company has approx. 500 employees, 45 production machines and an annual energy demand of about 8 Mio. kWh.
The new building (20,500 m2 production and 15,000 m2 office and representative areas) should unite the demands of energy efficiency and flexibility of
Conclusion
The proposed co-simulation provides an applicable tool for predicting the energy demand of production facilities in the early planning phases. The case study showed that this approach highlights the dependencies between the sub-systems and thus helps to identify further saving potentials compared to analyzing isolated systems. The presented co-simulation still allows domains to use their preferred simulation tools.
However, the coupled simulation approach presupposes specific requirements to the
Acknowledgements
The research presented has been funded by Klima- und Energiefonds within the program Neue Energien 2020 (grant no. 840746). The authors gratefully acknowledge the work of all project partners.
References (9)
- et al.
Integrated Process and System Modelling for the Design of Material Recycling Systems
CIRP Annals – Manufacturing Technology
(2013) - et al.
Integrated Production and Utility System Approach for Optimizing Industrial Unit Operations
Energy
(2010) - et al.
Interaction of Manufacturing Process and Machine Tool
CIRP Annals–Manufacturing Technology
(2009) - et al.
Energy Efficient Production – A Holistic Modelling Approach
Cited by (55)
Data based analysis and improvement of energy efficiency in the automotive body shop
2021, Journal of Cleaner ProductionCyber-physical production system approach for energy and resource efficient planning and operation of plating process chains
2021, Journal of Cleaner ProductionThermal modelling of manufacturing processes and HVAC systems
2020, EnergyCitation Excerpt :The study concluded the necessity to specify heat gains from machines in building energy analysis, by increasing the quality and reliability of building simulations, as well as reducing safety margins in design. Methodologies and frameworks for analysing energy consumption of a machine level using discrete event simulation (DES) is a common theme seen in literature [6,28–31]. For example, Solding and Thollander [32] proposed a method of combing material flow analysis with energy and resource flows using DES, which was aimed at allowing reduction of peak loads and efficient production planning due to disregard for the dynamic nature of machining processes.
Energy efficiency optimisation in industrial processes: Integral decision support tool
2020, EnergyCitation Excerpt :Energy modelling by simulation of the process is the best suited technique for a specific manufacturing system [9,30]. Furthermore, this methodological approach may easily be adapted to the uncertainties or the high variability of the Non-Continuous Process (N-CP)s [24,31]. Energy modelling by simulation allows us to optimise the process and to identify the hidden gaps during the process.