Continuous Process Verification for Trustworthy Manufacturing

This project supports research to advance the trustworthiness of manufacturing systems. Manufacturing is undergoing a rapid transformation as factories increasingly rely on automation, intelligent decision making, and data-driven optimization to improve productivity, quality, and resilience. These advances depend on trustworthy systems that monitor and control physical manufacturing processes. If process measurements are compromised by cyberattacks, equipment failures, or sensing errors, manufacturers may unknowingly make incorrect decisions that reduce product quality, increase waste, disrupt production, and create safety risks. However, today’s manufacturing systems are designed primarily to maximize production efficiency rather than continuously verify the integrity of process information. This project addresses this fundamental challenge by enabling manufacturing systems to continuously verify that sensed data faithfully represent physical processes. The resulting advances will improve the security, resilience, and reliability of advanced manufacturing, facilitate the adoption of intelligent manufacturing technologies, educate the future workforce, and strengthen the nation’s economic competitiveness. The specific goal of the research is to develop a control-monitoring co-randomization framework for trustworthy manufacturing. The research investigates whether carefully designed stochastic control and monitoring actions can generate physical watermarks that reveal discrepancies caused by cyberattacks, equipment faults, or compromised sensing. The framework integrates randomized control strategies, adaptive process monitoring, statistical signal analysis, system identification, and predictive control to continuously validate process integrity while preserving production quality and operational efficiency. The framework will be evaluated on representative manufacturing platforms, including automated assembly systems and chemical production processes. By tightly coupling physical process dynamics with cybersecurity mechanisms, this research establishes the scientific foundations for manufacturing systems that can continuously validate the trustworthiness of process information, enabling more reliable automation and the next generation of intelligent manufacturing. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.