An Engineering Education Project: Using a Robot and Thermal Imaging to Automate and Analyze Ultrasonic Welding of Plastics
Robotics and prototyping are high-profile subjects in contemporary undergraduate engineering and technology education. Further, the advent of low-cost infrared cameras for thermal imaging provides a convenient means to visualize and analyze processes in unprecedented detail. Ultrasonic welding is an...
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Published in | Association for Engineering Education - Engineering Library Division Papers |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
Atlanta
American Society for Engineering Education-ASEE
23.06.2018
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Subjects | |
Online Access | Get full text |
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Summary: | Robotics and prototyping are high-profile subjects in contemporary undergraduate engineering and technology education. Further, the advent of low-cost infrared cameras for thermal imaging provides a convenient means to visualize and analyze processes in unprecedented detail. Ultrasonic welding is an attractive plastics manufacturing technology for medical devices, packaging, and other industries. In ultrasonic welding, ultrasonic waves are directed at interfaces between contacted component plastic parts to effect a localized melting and weld bond. Ultrasonic welding is ‘clean’, energy efficient, and fast (1 second per weld), but is typically not very flexible due to constraints on the horn and part shape. Here, we combine ultrasonic welding and robotics for a programmable welding station by attaching an ultrasonic horn (20 kHz, 1 to 600 W) to a robotic arm. As a laboratory exercise, students use thermal imaging and a dynamometer to measure forces applied to the workpiece, in order to monitor and optimize the robotic process for spot and seam welding acrylic plastic parts, and assess weld strength using a tensile stress instrument. The robotic ultrasonic welder finds application in a host student projects related to 3d printing and rapid prototyping of renewable energy projects (wind turbines, solar cell arrays) and microfluidic devices. Learning assessments and adaptation for dissemination will be discussed. |
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Bibliography: | ObjectType-Conference Proceeding-1 SourceType-Conference Papers & Proceedings-1 content type line 21 |