TY - GEN
T1 - Information Modeling for Digitalized Sustainability Assessment in Manufacturing
AU - Schneider, D.
AU - Macanás Azcona, C.
AU - Woerle, M.
AU - Reinhart, G.
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Amid growing pressures for sustainable operations, the manufacturing industry faces methodological, knowledge-related, and organizational challenges in employing existing Life Cycle Assessment (LCA) tools effectively. Addressing LCA’s limitations related to static data and complex system boundaries, this paper presents an information modeling framework designed to enhance LCA applications. The study adopts a systematic approach using Unified Modeling Language (UML) to organize and visualize LCA data efficiently, based on the ecoinvent database. This framework is prototypically implemented and tested in an industrial use case involving the assembly of video surveillance cameras, demonstrating its capability to support dynamical assessments of sustainability performance. Aiming at bridging LCA with advanced digital technologies that are based on information models and interfaces, this framework proposes a concept for more accurate and adaptive sustainability evaluations in manufacturing, offering a pathway towards more informed and responsive environmental management.
AB - Amid growing pressures for sustainable operations, the manufacturing industry faces methodological, knowledge-related, and organizational challenges in employing existing Life Cycle Assessment (LCA) tools effectively. Addressing LCA’s limitations related to static data and complex system boundaries, this paper presents an information modeling framework designed to enhance LCA applications. The study adopts a systematic approach using Unified Modeling Language (UML) to organize and visualize LCA data efficiently, based on the ecoinvent database. This framework is prototypically implemented and tested in an industrial use case involving the assembly of video surveillance cameras, demonstrating its capability to support dynamical assessments of sustainability performance. Aiming at bridging LCA with advanced digital technologies that are based on information models and interfaces, this framework proposes a concept for more accurate and adaptive sustainability evaluations in manufacturing, offering a pathway towards more informed and responsive environmental management.
KW - Digital Twin
KW - Environmental Management
KW - Life Cycle Assessment
KW - Sustainability in Manufacturing
KW - UML Class Diagram
UR - http://www.scopus.com/inward/record.url?scp=85218010577&partnerID=8YFLogxK
U2 - 10.1109/IEEM62345.2024.10857244
DO - 10.1109/IEEM62345.2024.10857244
M3 - Conference contribution
AN - SCOPUS:85218010577
T3 - IEEE International Conference on Industrial Engineering and Engineering Management
SP - 994
EP - 998
BT - IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2024
PB - IEEE Computer Society
T2 - 2024 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2024
Y2 - 15 December 2024 through 18 December 2024
ER -