SmartPilot: Agent-Based CoPilot for Intelligent Manufacturing
Project Description: In the fast-changing landscape of Industry 4.0, achieving efficiency, precision, and adaptability is crucial for optimizing manufacturing operations. While foundational models have shown promise in delivering such advanced solutions in certain domains, they often face challenges in industrial applications due to certain limitations. This work introduces SmartPilot, a custom, compact, and neurosymbolic co-pilot designed to achieve the above metrics in modern manufacturing processes. By leveraging a domain-specific, right-sized solution optimized for edge devices, SmartPilot enhances real-time decision-making capabilities on the factory floor. The system employs an agent-based architecture to predict anomalies, forecast demand, and provide domain-specific question-and-answer support. These agents operate within a robust architecture that ensures seamless interoperability with existing systems. This solution ensures the trustworthiness of manufacturing processes while optimizing for performance, reliability, safety, and efficiency. SmartPilot is currently deployed in two manufacturing facilities focused on rocket assembly and Vegemite production. The dataset, codes to reproduce the results, and supplementary materials are available at this link.
NSF-MAP: Neurosymbolic Multimodal Fusion for Robust and Interpretable Anomaly Prediction in Assembly Pipelines
Project Description: In modern assembly pipelines, identifying anomalies is crucial in ensuring product quality and operational efficiency. Conventional single-modality methods fail to capture the intricate relationships required for precise anomaly prediction in complex predictive environments with abundant data and multiple modalities. This project proposes a neurosymbolic AI and fusion-based approach for multi-modal anomaly prediction in assembly pipelines. We introduce a time series and image-based fusion mechanism that leverages decision-level fusion techniques. link.