TY - JOUR
T1 - Holistic System Modelling and Analysis for Energy-Aware Production
T2 - An Integrated Framework
AU - Hehenberger, Peter
AU - Leherbauer, Dominik
AU - Penas, Olivia
AU - Delabeye, Romain
AU - Patalano, Stanislao
AU - Vitolo, Ferdinando
AU - Rega, Andrea
AU - Alefragis, Panayiotis
AU - Birbas, Michael
AU - Birbas, Alexios
AU - Katrakazas, Panagiotis
N1 - Funding Information:
This research was funded by the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement No. 958478.
Publisher Copyright:
© 2023 by the authors.
PY - 2023/2
Y1 - 2023/2
N2 - 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 basis of 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 an industrial context. As a result, this integrated conceptual framework offers the possibility of optimizing the production system, in relation to different energy flexibility criteria.
AB - 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 basis of 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 an industrial context. As a result, this integrated conceptual framework offers the possibility of optimizing the production system, in relation to different energy flexibility criteria.
KW - digital transformation
KW - digital twin
KW - energy management
KW - life cycle assessment
KW - sustainability
UR - http://www.scopus.com/inward/record.url?scp=85149206255&partnerID=8YFLogxK
U2 - 10.3390/systems11020100
DO - 10.3390/systems11020100
M3 - Article
AN - SCOPUS:85149206255
SN - 2079-8954
VL - 11
JO - Systems
JF - Systems
IS - 2
M1 - 100
ER -