doi: 10.18178/ijimt.2026.17.2.981
Towards a Systematic Dynamic Calculation of Material Carbon Footprints Through Harmonized Material Taxonomies and Enterprise Resource Planning Data Integration
2. KRONE Group, Spelle, Germany
3. Deutsches Forschungszentrum für Künstliche Intelligenz GmbH (DFKI), Marine Perception, Oldenburg, Germany
Email: naila.rana.andira@offis.de (N.R.A.); philipp.sander2@krone.de (P.S.); alexandra.pehlken@dfki.de (A.P.)
*Corresponding author
Manuscript received November 20, 2025; accepted March 12, 2026; published July 28, 2026
Abstract—Industry makes up the largest contribution to Greenhouse Gas (GHG) emissions, with three-quarters of global GHG emissions derived from it. Industrial GHG emissions themselves have been growing faster since the 2000s than any other sector due to an increase in material extraction and production as its demand exceeds economic and population growth. A slight change in procurement could lead to a fluctuation in products’ GHG emissions, especially in large, complex products or systems with a short cycle. This creates a problem, where additional effort is required in the data collection processes. At the same time, state-of-the-art technologies had been introduced to the manufacturing environment to capture more accurate data. In this paper, we incorporated an event-based architecture alongside the Enterprise Resource Planning (ERP) system to bring material and emission data into a dynamic visualization tool. This method enables the calculation of material GHG emissions based on each order from the ERP system, providing a more accurate and detailed estimation and result.
Keywords—material emission, Dynamic Life Cycle Assessment (LCA), event-based architecture
Cite: Naila Rana Andira, Philipp Sander, and Alexandra Pehlken, "Towards a Systematic Dynamic Calculation of Material Carbon Footprints Through Harmonized Material Taxonomies and Enterprise Resource Planning Data Integration," International Journal of Innovation, Management and Technology, vol. 17, no. 2, pp. 7-11, 2026.
Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).