Abstract
The manufacturing industry is responsible for a large share of global environmental impacts (e.g., greenhouse gas emissions) that can mainly be tracked back to energy demand. This energy demand is determined by a diversity of processes and machines, which dynamically interact in process chains and with other factory elements such as technical building services (TBS). Given that, system-oriented material flow simulation with inclusion of energy aspects bears the potential to support the energy transition of industry through fostering both energy efficiency and substitution towards renewable resources. The chapter addresses the necessary background as well as common aspects in the context of energy-oriented manufacturing system simulation. Four manufacturing case studies underline the feasibility and potential of available simulation approaches for improving energy-related environmental impacts and also costs. Additionally, an outlook towards potential future research steps is given.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Dehning P, Blume S, Dér A, Flick D, Herrmann C, Thiede S (2019) Load profile analysis for reducing energy demands of production systems in non-production times. Appl Energy 237:117–130
Dér A, Kaluza A, Reimer L, Herrmann C, Thiede S (2022) Integration of energy oriented manufacturing simulation into the life cycle evaluation of lightweight body parts. Int J Precis Eng Manuf-Green Technol 9:899–918
Ellingsen LAW, Majeau-Bettez G, Singh B, Srivastava AK, Valøen LO, Strømman AH (2014) Life cycle assessment of a lithium-ion battery vehicle pack. J Ind Ecol 18(1):113–124
Gebler M, Cerdas JF, Thiede S, Herrmann C (2020) Life cycle assessment of an automotive factory: identifying challenges for the decarbonization of automotive production—A case study. J Clean Prod 270:122330
Graßl MA (2014) Bewertung der Energieflexibilität in der Produktion. Ph.D. thesis, TU München, Werkzeugmaschinen und Betriebswissenschaften, München
Herrmann C, Thiede S, Kara S, Hesselbach J (2011) Energy oriented simulation of manufacturing systems—concept and application. CIRP Ann 60(1):45–48
Herrmann C, Posselt G, Thiede S (2013) Energie- und hilfsstoffoptimierte Produktion. Springer, Berlin Heidelberg
IPCC (2014) Climate Change 2014: mitigation of climate change. Contribution of working group iii to the fifth assessment report of the intergovernmental panel on climate change. Cambridge University Press, Cambridge
Klocke F, König W (2006) Fertigungsverfahren: Umformen. Springer, Berlin Heidelberg
Kwade A, Haselrieder W, Leithoff R, Modlinger A, Dietrich F, Droeder K (2018) Current status and challenges for automotive battery production technologies. Nat Energy 3(4):290–300
Labbus I (2021) Cyber-physische Produktionssysteme für die energieeffiziente Komponentenproduktion. Springer Fachmedien, Wiesbaden
Labbus I, Schmidt C, Dér A, Herrmann C, Thiede S (2018) Automated production data integration for energy-oriented process chain design. Procedia CIRP 72:551–556
Sauer A, Abele E, Buhl HU (2019) Energieflexibilität in der deutschen Industrie: Ergebnisse aus dem Kopernikus-Projekt – Synchronisierte und energieadaptive Produktionstechnik zur flexiblen Ausrichtung von Industrieprozessen auf eine fluktuierende Energieversorgung (SynErgie). Fraunhofer Verlag, Stuttgart
Schmidt C (2021) Planning of eco-efficient process chains for automotive component manufacturing. Springer, Berlin Heidelberg
Schmidt C, Labbus I, Herrmann C, Thiede S (2017) Framework of a modular tool box for the design of process chains in automotive component manufacturing. Procedia CIRP 63:739–744
Schönemann M (2017) Multiscale simulation approach for battery production systems. Springer International Publishing, Cham
Schönemann M, Bockholt H, Thiede S, Kwade A, Herrmann C (2019) Multiscale simulation approach for production systems. Int J Adv Manuf Technol 102(5):1373–1390
Sihn W, Sobottka T, Heinzl B, Kamhuber F (2018) Interdisciplinary multi-criteria optimization using hybrid simulation to pursue energy efficiency through production planning. CIRP Ann 67(1):447–450
Sobottka T, Kamhuber F, Rössler M, Sihn W (2018) Hybrid simulation-based optimization of discrete parts manufacturing to increase energy efficiency and productivity. Procedia Manuf 21:413–420
Sobottka T, Kamhuber F, Heinzl B (2020) Simulation-based multi-criteria optimization of parallel heat treatment furnaces at a casting manufacturer. J Manuf Mater Process 4(3):94. https://doi.org/10.3390/jmmp4030094
Stoldt J, Schlegel A, Franz E, Langer T, Putz M (2013) Generic energy-enhancement module for consumption analysis of manufacturing processes in discrete event simulation. In: Nee A, Song B, Ong SK (eds) Re-engineering manufacturing for sustainability. Springer, Singapore, pp 165–170
Stoldt J, Prell B, Rabe M, Wenzel S, Thiede S (2021) A criteria-based database for research and applications of energy-oriented simulation in production and logistics. In: Schuderer P, Franke J (eds) Simulation in Produktion und Logistik Cuvillier, Göttingen Germany, pp 93–102
Stoldt J, Prell B, Schlegel A, Putz M (2017) Modellierung von volatilen erneuerbaren Energieerzeugern und Energiespeichern in Siemens Plant Simulation. In Wenzel S, Peter T (eds) Simulation in Produktion und Logistik 2017. Kassel University Press, Kassel
Thiede S (2012) Energy efficiency in manufacturing systems. Springer, Berlin Heidelberg
Thiede S (2021) Digital technologies, methods and tools towards sustainable manufacturing: does Industry 4.0 support to reach environmental targets? Procedia CIRP 98:1–6
Thiede S, Seow Y, Andersson J, Johansson B (2013) Environmental aspects in manufacturing system modelling and simulation—state of the art and research perspectives. CIRP J Manuf Sci Technol 6(1):78–87
Thiede S, Turetskyy A, Kwade A, Kara S, Herrmann C (2019) Data mining in battery production chains towards multi-criterial quality prediction. CIRP Ann 68(1):463–466
Thomitzek M, von Drachenfels N, Cerdas F, Herrmann C, Thiede S (2019) Simulation-based assessment of the energy demand in battery cell manufacturing. Procedia CIRP 80:126–131
Verein Deutscher Ingenieure (2014) VDI Guideline 3633 Simulation of systems in materials handling, logistics and production—Part 1. Fundamentals. Beuth, Berlin
Walther J, Weigold M (2021) A systematic review on predicting and forecasting the electrical energy consumption in the manufacturing industry. Energies 14(4):968. https://doi.org/10.3390/en14040968
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Thiede, S., Dér, A., Münnich, M., Sobottka, T. (2024). Manufacturing. In: Wenzel, S., Rabe, M., Strassburger, S., von Viebahn, C. (eds) Energy-Related Material Flow Simulation in Production and Logistics. Springer, Cham. https://doi.org/10.1007/978-3-031-34218-9_2
Download citation
DOI: https://doi.org/10.1007/978-3-031-34218-9_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-34217-2
Online ISBN: 978-3-031-34218-9
eBook Packages: EngineeringEngineering (R0)