2024 ASEE Annual Conference & Exposition

Technology is changing at a much faster rate than ever. We call this the fourth industrial revolution (Industry 4.0). In the authors’ community colleges and workforce development programs, instructors focus on hands-on learning for high-level courses, including machine vision and capstone courses. Often the learning experience is hindered by lack of resources. To introduce Industry 4.0 concepts to students, a low-cost automated system for sorting candy that uses a portable gantry robotic system with machine vision was developed. This system makes Industry 4.0 concepts—such as Internet of things, smart manufacturing, cloud based manufacturing, and industrial Internet—more tangible and applicable to our courses.
Existing work on candy sorting machines can be broadly divided into two categories: optical sorting and mechanical sorting. Optical sorting machines use camera and machine vision algorithms to identify and sort candies by color, shape, size, and flavors; these are typically very fast and accurate. Mechanical sorting machines use a physical mechanism and gates with color sensors to do the sorting; these are typically slower rate and less accurate.
The objectives of the work described in this paper are to 1) develop a low-cost portable gantry robotic system with machine vision; 2) design lesson plans and activities for advanced programing and machine learning subjects and outreach to high schools; and 3) evaluate the impact of the system and lesson plans and make suggestions for future improvements.
Initial evaluation results suggest that the system and lesson plans have a positive impact on student learning in advanced manufacturing and machine learning. Future work includes using the system for outreach to local high school faculty, investigating which subjects the system can be used to teach, and using the system to help introduce project-based learning in dual credit courses by conducting workshops with high schools and college instructors.