2025 ASEE Annual Conference & Exposition

Educational Automated Manufacturing Cobot Work Cell in Conjunction with Machine Vision

Presented at Manufacturing Division (MFG) Technical Session 6

This paper presents the design, construction, and programming of an automated collaborative robot (cobot) work cell in conjunction with machine vision, specifically tailored for educational purposes within STEM fields. The work cell integrates various manufacturing machinery on an educational level into a cohesive learning module, providing students with a practical understanding of the operations involved in a modern manufacturing work environment. The primary objective is to offer engineering students direct exposure to integrated equipment functionalities, including a conveyor belt for part transport, a machine vision system with a photoelectric sensor array for part detection and quality assurance, a 6-degree-of-freedom cobot, and a 3D printer, which is replaceable to facilitate easy transitions between different technologies. Additionally, the project is designed to be adaptable, accommodating ongoing technological advancements and thus expanding the range of topics and experiences available to students. This setup serves as a versatile educational tool, enhancing the learning experience by bridging theoretical knowledge with hands-on practice in manufacturing processes.

Authors

Dr. Richard Y Chiou Drexel University [biography]

Dr. Richard Chiou is Professor within the Engineering Technology Department at Drexel University College of Engineering, Philadelphia, USA. He received his Ph.D. degree in the G.W. Woodruff School of Mechanical Engineering at Georgia Institute of Technology.
Prof. Tzu-liang Bill Tseng University of Texas at El Paso [biography]

Dr. Bill Tseng is a Professor and Chair of the Department of Industrial, Manufacturing, and Systems Engineering at UTEP. He is also a Director of the Research Institute for Manufacturing & Engineering Systems, the host institute of TMAC.
Dr. Md Fashiar Rahman http://orcid.org/0000-0002-0437-2587 University of Texas at El Paso [biography]

Dr. Md Fashiar Rahman is an Assistant Professor of the Industrial, Manufacturing and Systems Engineering (IMSE) Department at The University of Texas at El Paso. He holds a Ph.D. degree in Computational Science Program. He has years of research experience in different projects in the field of image data mining, machine learning, deep learning, and computer simulation for industrial and healthcare applications. In addition, Dr. Rahman has taught various engineering courses in industrial and manufacturing engineering. His research area covers advanced quality technology, AI application in smart manufacturing, health care applications, computational intelligence/data analytics, and decision support systems.
Dr. Yalcin Ertekin Drexel University [biography]

Yalcin Ertekin, Ph.D., CMfgE, CQE is a clinical professor in the College of Engineering, Department of Engineering Leadership and Society at Drexel University, Philadelphia, and serves as the Associate Department Head for Undergraduate Studies for the Engineering Technology program. He received his BS degree from Istanbul Technical University in Turkey, an MSc in Production Management from the University of Istanbul, an MS in Engineering Management, and an MS and Ph.D. in Mechanical Engineering from the University of Missouri-Rolla. Ertekin has also been a Certified Manufacturing Engineer (CMfgE), awarded by the Society of Manufacturing Engineers (SME) since 2001, and a Certified Quality Engineer (CQE) awarded by the American Society for Quality (ASQ) since 2004. In addition to positions in the automotive industry, Dr. Ertekin has held faculty positions at Western Kentucky University and Trine University. He later joined Drexel University's College of Engineering as an associate clinical professor and has been instrumental in course development and the assessment and improvement of the Engineering Technology (ET) curriculum, including integrated laboratories, project-based learning, and practicum-based assessment. Ertekin serves as the faculty advisor for the student chapter of the Society of Manufacturing Engineers (S058) and is a member of the College’s Undergraduate Curriculum Committee. Involved in research, Ertekin has received funding from the National Science Foundation (NSF), private foundations, and industry. His research has focused on the improvement of manufacturing laboratories and curricula and the adoption of process simulation into machining and additive manufacturing practices. His areas of expertise are in CAD/CAM, manufacturing processes, machine and process design with CAE methods, additive and subtractive manufacturing, quality control and lean manufacturing.

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 22, 2025, and to all visitors after the conference ends on June 25, 2025

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