Governance of Real Time Sustainability KPIS in Manufacturing – Bi, IIoT and AI Enhanced Lean Six Sigma
References
- Bertsimas, D., & Kallus, N. (2020). From predictive to prescriptive analytics. Management Science, 66(3), 1025–1044.
- Bunse, K., Vodicka, M., Schönsleben, P., Brülhart, M., & Ernst, F. O. (2011). Integrating energy efficiency performance in production management: Gap analysis between industrial needs and scientific literature. Journal of Cleaner Production, 19(6–7), 667–679.
- Gibson Brandon, R., Krueger, P., & Mitali, S. F. (2021). The sustainability footprint of institutional investors: ESG driven price pressure and performance. Swiss Finance Institute Research Paper No. 17-05, ECGI Finance Working Paper.
- International Organization for Standardization. (2018). ISO 50001:2018 Energy management systems: Requirements with guidance for use. ISO.
- Kotsantonis, S., & Serafeim, G. (2019). Four things no one will tell you about ESG data. Journal of Applied Corporate Finance, 31(2), 50–58.
- Lee, J., Bagheri, B., & Kao, H.-A. (2015). A cyber-physical systems architecture for Industry 4.0- based manufacturing systems. Manufacturing Letters, 3, 18–23.
- Menghi, R., Papetti, A., Germani, M., & Marconi, M. (2019). Energy efficiency of manufacturing systems: A review of energy assessment methods and tools. Journal of Cleaner Production, 240, 118276.
-
Montgomery, D. C. (2019). Introduction to statistical quality control (8th ed.). Wiley.
Montgomery D. C. ( 2019 ). Introduction to statistical quality control (8th ed.) . Wiley.
- Sarfraz, M., Ivascu, L., Artene, A. E., Bobitan, N., Dumitrescu, D., Bogdan, O., & Burca, V. (2023). The relationship between firms’ financial performance and performance measures of circular economy sustainability: An investigation of the G7 countries. Economic Research–Ekonomska Istraživanja, 36(1), 2545–2572.
- Shah, W. U. H., Yasmeen, R., Sarfraz, M., & Ivascu, L. (2023). The repercussions of economic growth, industrialization, foreign direct investment, and technology on municipal solid waste: Evidence from OECD economies. Sustainability, 15(1), 836
- Wang, J., Xu, C., Zhang, J., & Zhong, R. Y. (2022). Big data analytics for intelligent manufacturing Systems, 62, 738–752.
- World Resources Institute, & World Business Council for Sustainable Development. (2015). GHG Protocol Scope 2 guidance: An amendment to the GHG Protocol Corporate Standard. Greenhouse Gas Protocol.
- Xu, L. D., & Duan, L. (2019). Big data for cyber-physical systems in Industry 4.0: A survey. Enterprise Information Systems, 13(2), 148–169.
- Zhang, Y., Ren, S., Liu, Y., & Si, S. (2017). A big data analytics architecture for cleaner manufacturing and maintenance processes of complex products. Journal of Cleaner Production, 142, 626–641.
DOI: https://doi.org/10.2478/picbe-2026-0116 | Journal eISSN: 2558-9652
Language: English
Page range: 1517 - 1527
Published on: Jul 20, 2026
Published by: Bucharest University of Economic Studies
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year
Keywords:
Related subjects:
© 2026 Nicoleta-Mihaela CASANEANU (DASCALU), Marius PISLARU1, Elena-Lidia ALEXA, Geanina GIOSAN, published by Bucharest University of Economic Studies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.