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Constructing Reconfigurable and Affordable Robotic Arm Platform to Teach Robotics and Automation

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Conference

2024 ASEE Annual Conference & Exposition

Location

Portland, Oregon

Publication Date

June 23, 2024

Start Date

June 23, 2024

End Date

July 12, 2024

Conference Session

Robotics and Circuits

Tagged Division

Computers in Education Division (COED)

Tagged Topic

Diversity

Permanent URL

https://peer.asee.org/47069

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Paper Authors

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Carl Joseph Murzynski Pennsylvania State University, Behrend College

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Carl Murzynski is an undergraduate student in Electrical Engineering at Pennsylvania State University, The Behrend College. He specializes in robotics and automation, actively contributing to research projects aimed at advancing these fields.

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Hussein - Abdeltawab Wake Forest University

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Omar Ashour Pennsylvania State University, Behrend College Orcid 16x16 orcid.org/0000-0003-3775-6445

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Dr. Omar Ashour is an Associate Professor of Industrial Engineering at Pennsylvania State University, The Behrend College. Dr. Ashour received the B.S. degree in Industrial Engineering/Manufacturing Engineering and the M.S. degree in Industrial Engineering from Jordan University of Science and Technology (JUST) in 2005 and 2007, respectively. He received his M.Eng. degree in Industrial Engineering/Human Factors and Ergonomics and a Ph.D. degree in Industrial Engineering and Operations Research from The Pennsylvania State University (PSU) in 2010 and 2012, respectively. Dr. Ashour was the inaugural recipient of William and Wendy Korb Early Career Professorship in Industrial Engineering in 2016. Dr. Ashour’s research areas include data-driven decision-making, modeling and simulation, data analytics, immersive technologies, and process improvement. He contributed to research directed to improve design and engineering education.

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Ahmed Sammoud Pennsylvania State University, Behrend College

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Ahmed Sammoud is a Computer Science and Software Engineering faculty at Pennsylvania State University, The Behrend College. Ahmed is an avid computer scientist and engineer interested in reconfigurable computing, operating systems, video processing, Machine Learning, and Real-Time systems.

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Abstract

Since its announcement in 2011, the concepts of Industry 4.0 (I4.0) have moved from theory to real-world applications, and the need for skilled engineers has grown. Therefore, many colleges and universities are strategizing ways to provide students with hands-on experiences to develop the needed practical skills in industry. One of the pillars of I4.0 is human-machine interaction which includes robotics and automation. Undergraduate degrees need to provide applied knowledge of robots that use modern controllers and other integrated hardware rather than the classic robotic design. The curriculum should provide the students with real-world experiences with real hardware. This paper presents the steps of designing and constructing a reconfigurable and affordable industrial robotic arm platform that can be used to teach robotics and automation concepts to many engineering fields. This work presents a step-by-step construction procedure, mechanical and electrical setup, and hardware resources used to build the platform. The cost of the platform was less than $10K, which makes it affordable. Several majors in engineering and engineering technology can use the reconfigurable platform to teach many concepts of the I4.0. For example, Industrial Engineering students can use it to teach manufacturing systems concepts, and Computer Science and Engineering students can use it to teach robotics and automation concepts. We used the platforms in an operating systems and systems programming course in the Fall 2023 semester. The results of the system usability score showed a high usability score (A+) for these platforms.

Murzynski, C. J., & Abdeltawab, H., & Ashour, O., & Sammoud, A. (2024, June), Constructing Reconfigurable and Affordable Robotic Arm Platform to Teach Robotics and Automation Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. https://peer.asee.org/47069

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