| dc.description.abstract | The Fiber Extrusion Device (FrED) serves as a hands-on learning tool and laboratory experience, simulating the continuous fiber draw process to provide insights into data acquisition, control systems, and smart manufacturing. This system enables learners to conduct experiments, manipulate manufacturing parameters and control systems, gather data, and conduct analyses. While successful classroom activities have been conducted using FrED, the preceding model's cost precludes widespread distribution for remote learning, a growing trend in education.
This thesis encompasses a series of enhancements to FrED, aimed at refining its stability, cooling mechanisms, modularity, noise reduction, size, and overall functionality. Pulley variations were introduced to enhance fiber stability. Cooling strategies and pulley system's flexibility were optimized for the stability of the fiber, and noise reduction measures focused on the gear system. The camera system underwent significant redesigning, enabling more precise fiber diameter measurement. In addition to that, a shift from Teensy to Raspberry Pi improved system integration. Code for extrusion and gear motors, heater, and thermistor was rewritten, alongside redesigns of the extrusion system, PCB, and camera module.
The final FrED design accomplished a 42% cost reduction ($159) and a weight reduction of 25% (1.7 kg) with optimal fiber cooling and stability, seamless integration of computer vision for diameter measurement and data collection was achieved, enabling its application in PID control and enhancing the teaching of machine learning principles. | |
