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A System-Level Energy-Efficient Digital Twin Framework for Runtime Control of Batch Manufacturing Processes
To improve the scheduling and control of batch manufacturing processes, we propose a system-level energy-efficient Digital Twin framework that considers Time-of-Use (TOU) energy pricing for runtime decision-making.
Opportunities and Challenges to Integrate Artificial Intelligence into Manufacturing Systems: Thoughts from a Panel Discussion
Three overarching themes emerged from the panel discussion.
A Model Predictive Control Framework for Improving Risk-Tolerance of Manufacturing Systems
The need for control strategies that can address dynamic system uncertainty is becoming increasingly important.
Risk-Averse Model Predictive Control for Priced Timed Automata
In this paper, we propose a Risk-Averse Priced Timed Automata (PTA) Model Predictive Control (MPC) framework to increase flexibility of cyber-physical systems.
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