6 papers
CausalTrace: A Neurosymbolic Causal Analysis Agent for Smart Manufacturing
Chathurangi Shyalika, Aryaman Sharma, Fadi El Kalach +4
Modern manufacturing environments demand not only accurate predictions but also interpretable insights to process anomalies, root causes, and potential interventions. Existing AI s…
ViSTR-GP: Online Cyberattack Detection via Vision-to-State Tensor Regression and Gaussian Processes in Automated Robotic Operations
Navid Aftabi, Philip Samaha, Jin Ma +3
Industrial robotic systems are central to automating smart manufacturing operations. Connected and automated factories face growing cybersecurity risks that can potentially cause i…
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…
AssemAI: Interpretable Image-Based Anomaly Detection for Manufacturing Pipelines
Renjith Prasad, Chathurangi Shyalika, Ramtin Zand +4
Anomaly detection in manufacturing pipelines remains a critical challenge, intensified by the complexity and variability of industrial environments. This paper introduces AssemAI,…