{"id":10765,"date":"2026-07-02T13:09:05","date_gmt":"2026-07-02T13:09:05","guid":{"rendered":"https:\/\/affiliate.wcu.edu\/cet-news\/?p=10765"},"modified":"2026-07-02T13:59:58","modified_gmt":"2026-07-02T13:59:58","slug":"building-the-future-of-smart-manufacturing-inside-engr-493s-ai-robotics-projects","status":"publish","type":"post","link":"https:\/\/affiliate.wcu.edu\/cet-news\/blog\/2026\/07\/02\/building-the-future-of-smart-manufacturing-inside-engr-493s-ai-robotics-projects\/","title":{"rendered":"Building the Future of Smart Manufacturing: Inside ENGR 493\u2019s AI + Robotics Projects"},"content":{"rendered":"

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Students in Western Carolina University\u2019s ENGR 493 course, \u201cAI and Computer Vision for Smart Manufacturing,\u201d gained hands-on experience at the intersection of artificial intelligence and robotics\u2014preparing them for careers in a rapidly evolving industrial landscape.<\/span>\u00a0<\/span><\/p>\n

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Taught by Dr. Abdallah Abdallah, associate professor in the WCU College of Engineering<\/a> <\/strong>and a certified NVIDIA Deep Learning Institute (DLI) instructor, assisted by Co-PI Dr. Islam Elgarhy, assistant professor, the course challenged students to design, program, and integrate robotic systems capable of automating real-world manufacturing processes.<\/span>\u00a0<\/span><\/p>\n

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Working in teams, students developed three distinct robotic systems, which they named HULK, MEDUSA, and OPTIMUS.<\/span>\u00a0<\/span><\/p>\n

One\u00a0team built\u00a0<\/span>MEDUSA<\/span><\/b>, training two identical robots to collaborate to\u00a0identify\u00a0an item of a certain color on a conveyor belt and remove it\u2014simulating the removal of defective items from an automated production line. Another team developed\u00a0<\/span>HULK<\/span><\/b>, which used a machine learning classification model to recognize utensils as visual cues, then pick and reposition the\u00a0specific colored\u00a0block\u00a0designated\u00a0to each cue. A third team created\u00a0<\/span>OPTIMUS\u00a0<\/span><\/b>(a mobile vehicle equipped with camera and robot arm), focused on object detection and motion tracking; using an AI model, the robot\u00a0identified\u00a0and followed a ball, then executed a coordinated sequence to approach and retrieve it.<\/span>\u00a0<\/span><\/p>\n

Students described the experience as both challenging and rewarding, highlighting the complexity of integrating hardware and software while working under real-world constraints.<\/span>\u00a0<\/span><\/p>\n

The course is supported by a $35,000 Undergraduate Research Program Award from the UNC System, which enables students to gain valuable, hands-on research experience. This initiative reflects the growing importance of Industry 4.0 technologies, where AI-powered systems are increasingly used in factories and warehouses.<\/span><\/p>\n

[\/et_pb_text][et_pb_testimonial author=” Dr. Abdallah Abdallah” job_title=”Associate Professor” company_name=”WCU College of Engineering” _builder_version=”4.27.7″ _module_preset=”default” global_colors_info=”{}”]\u201cThis course puts students right at the intersection of AI, robotics, and manufacturing \u2014 the exact skills our regional and national industries are asking for. It was challenging, and honestly a lot of fun. Giving undergraduates the chance to design and test real intelligent systems is how we prepare them to lead in Industry 4.0.\u201d<\/span><\/span>
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During the summer, some students will continue to expand these projects, developing more advanced AI-based control algorithms and exploring additional applications for robotic automation.<\/span><\/p>\n

As manufacturing continues to evolve, courses like ENGR 493 ensure that students graduate with the interdisciplinary skills needed to design, program, and\u00a0maintain\u00a0the intelligent systems shaping the future.<\/span>\u00a0<\/span><\/p>\n

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