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Board # 54: Design of Remotely Accessible Automated Systems to Enhance Industrial Automation Education

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2017 ASEE Annual Conference & Exposition


Columbus, Ohio

Publication Date

June 24, 2017

Start Date

June 24, 2017

End Date

June 28, 2017

Conference Session

NSF Grantees Poster Session

Tagged Topic

NSF Grantees Poster Session

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Paper Authors


Sheng-Jen Hsieh Texas A&M University

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Dr. Sheng-Jen (“Tony”) Hsieh is a Professor in the Dwight Look College of Engineering at Texas A&M University. He holds a joint appointment with the Department of Engineering Technology and the Department of Mechanical Engineering. His research interests include engineering education, cognitive task analysis, automation, robotics and control, intelligent manufacturing system design, and micro/nano manufacturing. He is also the Director of the Rockwell Automation laboratory at Texas A&M University, a state-of-the-art facility for education and research in the areas of automation, control, and automated system integration.

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Industrial scale automated systems can be used to provide authentic learning experiences for students. Skill sets needed to design and build automated systems are essential to our national economy. However, students often have limited access to equipment due to limitations in available lab time and available equipment. This paper describes the design of three web-based automated systems (material sorting system, pick-and-place automated system, and remote-control of robot system) and preliminary evaluation of the systems. Preliminary findings include 1) students seemed interested and intrigued by the set up; 2) there is a time-delay between the control action and the image being presented over the webcam; and 3) students want more time to use the system. Future directions include evaluating instructional effectiveness, identifying which aspects of the experience help students learn, and determining optimal time frames for completing assignments.

Hsieh, S. (2017, June), Board # 54: Design of Remotely Accessible Automated Systems to Enhance Industrial Automation Education Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. 10.18260/1-2--27878

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