<div class="csl-bib-body">
<div class="csl-entry">Nagel, L., Gerstbauer, R., Harutyunyan, L., Trautner, T., Bleicher, F., & Weigold, M. (2025). A Service-Based Approach for Predicting the Carbon Footprint in the Supply Chain of Plastic Injection-Moulded Parts During Product Development. In H. Kohl, G. Seliger, F. Dietrich, & V. Ha Thuc (Eds.), <i>Decarbonizing Value Chains : Proceedings of the 20th Global Conference on Sustainable Manufacturing (GCSM 2024), October 9–11, 2024, Ho Chi Minh City, Vietnam</i> (pp. 192–199). Springer Cham. https://doi.org/10.1007/978-3-031-93891-7_22</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/224174
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dc.description.abstract
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.
en
dc.description.sponsorship
FFG - Österr. Forschungsförderungs- gesellschaft mbH
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dc.description.sponsorship
FFG - Österr. Forschungsförderungs- gesellschaft mbH
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dc.language.iso
en
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dc.relation.ispartofseries
Lecture Notes in Mechanical Engineering
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dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
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dc.subject
CO₂ emissions
en
dc.subject
sustainable development
en
dc.subject
data spaces
en
dc.subject
Gaia-X
en
dc.title
A Service-Based Approach for Predicting the Carbon Footprint in the Supply Chain of Plastic Injection-Moulded Parts During Product Development
Decarbonizing Value Chains : Proceedings of the 20th Global Conference on Sustainable Manufacturing (GCSM 2024), October 9–11, 2024, Ho Chi Minh City, Vietnam
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tuw.peerreviewed
true
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tuw.relation.publisher
Springer Cham
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tuw.relation.publisherplace
Cham
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tuw.project.title
EuProGigant – Europäisches Produktionsgiganet zur kalamitätsmindernden Selbstorchestrierung von Wertschöpfungs- und Lernökosystemen
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tuw.project.title
EuProGigant - Interoperable, dezentrale Daten- und Service-Ökosysteme zur Befähigung nachhaltiger Produktionsräume
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tuw.researchTopic.id
I6
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tuw.researchTopic.id
E6
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tuw.researchTopic.name
Digital Transformation in Manufacturing
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tuw.researchTopic.name
Sustainable Production and Technologies
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tuw.researchTopic.value
50
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tuw.researchTopic.value
50
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tuw.publication.orgunit
E311-01-3 - Forschungsgruppe Steuerungstechnik und integrierte Systeme