The purpose of the exercise is truly multifaceted. We’d like to teach the students about digital twin technology, stepper motors, H-bridge, limit-switches, hardware hookup, calibration and PLC programming. The pedagogical framework for this student lab activity is grounded in problem-based and student-active learning, with segmentation as a key component. Segmentation involves breaking down complex tasks, concepts, or problems into smaller, manageable units that are logically connected. Each segment targets a specific sub-skill, enabling learners to master one part before progressing to the next.

The authors have used this assignment in their teaching for 3 years, about 150 students/hand-ins. Results are that the students seem to appreciate the modularity of the assignment, even if it is challenging. Furter the students appreciate the joy of seeing the wing physically move as intended from their own coding. As teachers we see that the students seem quite motivated by the assignment. they ask good questions and learn “the hard way” that a software simulator and hardware can be quite different.

In essence, the narrative about the fighter jet wing serves to give students some motivation and context it could be any stepper motor application.

This project addresses the power overload problem faced by a glass bottle manufacturing enterprise that expanded to five automated production lines and a glass-melting furnace. The existing power system, originally designed for smaller operations, could not withstand the transient current surges—five to eight times the normal level—generated when multiple high-power lines started simultaneously. Manual time-based scheduling was used to stagger production start-ups, but it lacked stability and real-time adaptability.

To solve this issue, a multidisciplinary team of instructors and students from Rui De International College collaborated with the company to design and implement a PLC-based intelligent control system for dynamic power load management. The system adopts a three-tier architecture comprising a data acquisition layer, a control layer, and a management layer integrating PLC logic control, sensor data acquisition, and HMI-based visualization. Four core modules were developed: intelligent staggered start, automated control logic, data analysis, and protection and alarm mechanisms.

Practical application demonstrated that the system effectively eliminated overload-induced shutdowns, stabilized current fluctuations, and improved reliability and production efficiency. With a total cost of approximately RMB 80,000–100,000—far below the RMB 500,000 required for transformer replacement—the solution proved both technically and economically advantageous. The project also exemplifies how vocational colleges can collaborate with industry to deliver innovative, low-cost smart manufacturing solutions while enhancing students’ applied automation skills and instructors’ practical teaching competence.

The 21st century industrial landscape is undergoing an unprecedented transformation, driven by artificial intelligence (AI), sustainable digitaliza-tion, and the rapid evolution of smart building technologies. These devel-opments are redefining how knowledge is generated, transferred, and ap-plied within both industrial and educational environments. This paper ex-plores the synergy between smart industry and education in the era of In-dustry 5.0 — an emerging paradigm emphasizing human-centric, resilient, and sustainable systems. Through an interdisciplinary analysis of European and global case studies, including initiatives in Germany and Ukraine, the study identifies effective models that integrate AI, smart infrastructure, and sustainability principles into educational ecosystems. Empirical evidence from university–industry collaborations demonstrates that such integration enhances technical competence, promotes creativity, and builds resilience within future-ready workforces. Drawing on the works of Koeberlein-Kerler (2021, 2023), who pioneered the concept of hybrid learning ecosys-tems and living laboratories for engineering education, the paper substanti-ates that the merging of smart industry and education is essential to achiev-ing the goals of sustainable innovation, digital inclusion, and professional adaptability.