School of Engineering Department of Chemical and Biological Engineering 74 Department of Chemical and Biological Engineering Monitoring of Molding Process via Integrated Sensor Development Supervisor: GAO, Furong / CBE Student: CHENG, Leong / CENG Course: UROP1100, Summer This paper compares the performance of Proportional-Integral-Derivative (PID) and Model Predictive Control (MPC) controllers in regulating dissolved oxygen concentration in a singlesludge wastewater treatment plant using the Activated Sludge Model No. 1 (ASM1). Through simulation-based experiments, we compare the control strategies' effectiveness in terms of Integral Absolute Error (IAE) and Rise Time. The results show that both PID and MPC controllers can maintain dissolved oxygen concentration within acceptable limits with MPC generally outperforming. The study also identifies some limitations, such as the need for more accurate sensor data and improved modeling techniques. Finally, the paper suggests potential areas for future research, including evaluating the impact of varying influent characteristics and assessing the monetary cost of implementing the control strategies. Monitoring of Molding Process via Integrated Sensor Development Supervisor: GAO, Furong / CBE Student: SHAO, Heyan / CENG Course: UROP1100, Fall Injection molding is a major material processing method used in the mass manufacture of plastic items. Acquiring real-time data during the manufacturing process is a rising trend for monitoring the injection molding process driven by Industry 4.0 requirements. The mold cavity where the plastic part is created contains the most pertinent information to the technological process itself. Nowadays, most manufacturing process parameters within the mold cavity are collected by sensors. Although there are numerous sensors available in the current market, those that are useful for in-mold measurements have certain peculiarities. This report aims to present a thorough overview of in-mold process monitoring tools and injection molding process control techniques.
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