At the heart of smart manufacturing is real-time semi-automatic decision-making. Such decisions are vital for optimizing production lines, e.g., reducing resource consumption, improving the quality of discrete manufacturing operations, and optimizing the actual products, e.g., optimizing the sampling rate for measuring product dimensions during production. Such decision-making relies on massive industrial data thus posing a real-time processing bottleneck.
CITATION STYLE
Rincon-Yanez, D., Gad-Elrab, M. H., Stepanova, D., Tran, K. T., Chu Xuan, C., Zhou, B., & Karlamov, E. (2023). Addressing the Scalability Bottleneck of Semantic Technologies at Bosch. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13998 LNCS, pp. 177–181). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-43458-7_33
Mendeley helps you to discover research relevant for your work.