Industrial Challenges for Automation Learning

Abstract

This paper presents an automation learning activity built around a real industrial problem proposed within a university-private sector collaboration, specifically the Michelin factory in Valladolid. The experience was conceived as a problem-based, competitive learning activity rather than as a conventional classroom exercise. Student teams had to analyse an authentic production-related challenge and prepare a technically grounded proposal involving robotics, computer vision, control engineering and artificial intelligence. The activity attracted 36 registered teams; 25 submitted a proposal, 4 reached the final defence stage, and one team won the competition. The finalist teams visited the industrial facilities, which helped students understand operational constraints, safety requirements and implementation feasibility. The educational impact was evaluated through a questionnaire completed by 30 participants. Results indicate a positive perception of the activity, with high scores for motivation, active involvement and teamwork. The paper discusses the learning design, the role of generative AI as a support tool, and the value of real industrial challenges for automation education.