78 citations · 179 across the 12 of their papers we have counts for
6 papers · 1 filter
NSF-MAP: Neurosymbolic Multimodal Fusion for Robust and Interpretable Anomaly Prediction in Assembly Pipelines
Chathurangi Shyalika, Renjith Prasad, Fadi El Kalach +4
In modern assembly pipelines, identifying anomalies is crucial in ensuring product quality and operational efficiency. Conventional single-modality methods fail to capture the intr…
Analog and Multi-modal Manufacturing Datasets Acquired on the Future Factories Platform V2
Ramy Harik, Fadi El Kalach, Jad Samaha +8
This paper presents two industry-grade datasets captured during an 8-hour continuous operation of the manufacturing assembly line at the Future Factories Lab, University of South C…
Time-Series Forecasting in Smart Manufacturing Systems: An Experimental Evaluation of the State-of-the-art Algorithms
Mojtaba A. Farahani, Fadi El Kalach, Austin Harper +3
TSF is growing in various domains including manufacturing. Although numerous TSF algorithms have been developed recently, the validation and evaluation of algorithms hold substanti…
Analog and Multi-modal Manufacturing Datasets Acquired on the Future Factories Platform
Ramy Harik, Fadi El Kalach, Jad Samaha +8
Two industry-grade datasets are presented in this paper that were collected at the Future Factories Lab at the University of South Carolina on December 11th and 12th of 2023. These…
Time-Series Classification in Smart Manufacturing Systems: An Experimental Evaluation of State-of-the-Art Machine Learning Algorithms
Mojtaba A. Farahani, M. R. McCormick, Ramy Harik +1
Manufacturing is gathering extensive amounts of diverse data, thanks to the growing number of sensors and rapid advances in sensing technologies. Among the various data types avail…
Time-Series Pattern Recognition in Smart Manufacturing Systems: A Literature Review and Ontology
Mojtaba A. Farahani, M. R. McCormick, Robert Gianinny +4
Since the inception of Industry 4.0 in 2012, emerging technologies have enabled the acquisition of vast amounts of data from diverse sources such as machine tools, robust and affor…