Smart Manufacturing Systems provide a vision of future manufacturing systems that incorporate highly dynamic physical systems, robust and responsive communications systems, and computing paradigms to maximize efficiency, enable mobility, promote flexibility, and realize the promises of the digital factory. Wireless technology is a key enabler of this vision. Key challenges to integrating wireless systems within the factory environment include identifying robust requirements for wireless networks; managing coexistence of a variety of networks within a finite electromagnetic spectrum; realizing spectrum-aware and power-aware distributed control systems, achieving high-reliability and low-latency; integrating spectrum awareness within the automation system; exploring co-design methodologies for control systems that are aware of the state of the underlying communications system; and defining repeatable testing and metrology methods for assessing performance. This project addresses these challenges by developing robust system requirements, system models, recommended architectures, metrology approaches for industrial wireless systems, test methods standardization, and guidelines for establishing trustworthy wireless systems within the agile and collaborative factory environment.
Through collaboration with industry and academia, we will continue to develop model architectures for high-priority industrial use cases that include mobile robotic and collaborative platforms. We will continue to select use cases based on industry input and our independent research. In this project we will:
Candell, R., Kashef, M., Montgomery, K., Liu, Y., & Foufou, S. (2022). Machine Learning Based Wireless Interference Estimation in a Robotic Force-Seeking Application. https://doi.org/10.6028/NIST.IR.8416
Kashef, M., Liu, Y., Montgomery, K., & Candell, R. (2021). Wireless Cyber-Physical Systems Performance Evaluation through a Graph Database Approach. Journal of computing and information science in engineering, 21(2), 10.1115/1.4048205. https://doi.org/10.1115/1.4048205.
R. Candell, K. Montgomery, S. Sudhakaran, M. Kashef, and D. Cavalcanti. Impacts of 802.1Qbv Time-sensitive Networking Schedules on the Physical Performance of a Leader-Follower Robot Lift Operation. Proceedings of the IEEE Industrial Electronics Conference 2023. In process.