Lukas Nagel
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Lukas Nagel has a total of 18 co-authors. Here are the top co-authors by number of shared publications:
- Matthias Weigold
Institute for Production Management, Technology and Machine Tools (PTW), Technical University of Darmstadt
3 shared publications - Stefan Seyfried
Technical University of Darmstadt
2 shared publications - Aikaterini Paraskevopoulou
University of Patras
1 shared publication - Astrid Weyand
Technical University of Darmstadt
1 shared publication - Daniel Fuhrländer-Völker
Institute of Production Management, Technology and Machine Tools (PTW), Technical University of Darmstadt, Darmstadt, Germany
1 shared publication - Fabian Gast
Institute for Production Management, Technology and Machine Tools (PTW), Technical University of Darmstadt, Otto-Berndt-Straße 2, 64287 Darmstadt, Germany
1 shared publication
Latest Publications
- 1 October 2025
- Published by Springer Nature
- p. 389-397
From Regulations to Compliance: Adapting a Learning Factory to Train SMEs on Sustainability Regulations
- 1 October 2025
- Published by Springer Nature
- p. 389-397
From Regulations to Compliance: Adapting a Learning Factory to Train SMEs on Sustainability Regulations
- 9 July 2025
- Published by Springer Nature
- p. 165-188
Monetarisierung einer industriellen Datenbasis
- Open Access
- 27 June 2025
- Published by Springer Nature
- p. 192-199
A Service-Based Approach for Predicting the Carbon Footprint in the Supply Chain of Plastic Injection-Moulded Parts During Product Development
Driven by the European Union’s commitment to achieving climate neutrality by 2050 and reducing EU emissions by 55% relative to 1990 levels by 2030, a critical assessment of manufacturing processes for their environmental impacts is necessary. During the strategic planning stage of product development and manufacturing, limited data is available to predict the environmental impacts across supply chains. However, decisions made at this phase significantly influence these impacts. This paper presents a data-provision method that aims to support decision-making in product development with quantifiable metrics of ecological sustainability. This is achieved through predicting carbon footprints, while leveraging the European data infrastructure Gaia-X, which enables secure service offerings and data sharing across the supply chain. The prediction service is implemented as a web application that facilitates the input and variation of hypothetical production scenarios. In a specific use-case, the method is applied to the supply chain of an injection-moulded cup. This concept offers a vision for carbon-optimized product development, enabling significant carbon avoidance in later production stages and showcasing the influence of different production parameters on the supply-chain carbon footprint.
- 27 June 2025
- Published by Springer Nature
- p. 192-199
Open AccessA Service-Based Approach for Predicting the Carbon Footprint in the Supply Chain of Plastic Injection-Moulded Parts During Product Development
Driven by the European Union’s commitment to achieving climate neutrality by 2050 and reducing EU emissions by 55% relative to 1990 levels by 2030, a critical assessment of manufacturing processes for their environmental impacts is necessary. During the strategic planning stage of product development and manufacturing, limited data is available to predict the environmental impacts across supply chains. However, decisions made at this phase significantly influence these impacts. This paper presents a data-provision method that aims to support decision-making in product development with quantifiable metrics of ecological sustainability. This is achieved through predicting carbon footprints, while leveraging the European data infrastructure Gaia-X, which enables secure service offerings and data sharing across the supply chain. The prediction service is implemented as a web application that facilitates the input and variation of hypothetical production scenarios. In a specific use-case, the method is applied to the supply chain of an injection-moulded cup. This concept offers a vision for carbon-optimized product development, enabling significant carbon avoidance in later production stages and showcasing the influence of different production parameters on the supply-chain carbon footprint.
- 11 July 2024
- Published by Springer Nature
- p. 321-328
A Learning Factory as a Competence Centre for Climate-Neutral Production
- 11 July 2024
- Published by Springer Nature
- p. 321-328
A Learning Factory as a Competence Centre for Climate-Neutral Production