The transition from Industry 4.0 to Industry 5.0 highlights the growing emphasis on human-centric innovation in manufacturing systems, underscoring the need for educational tools that foster creativity, critical thinking, and technical acumen. This study presents the design and implementation of a didactic game aimed at teaching Single-Minute Exchange of Dies (SMED), standard work procedures, and secondary lean principles such as waste reduction and continuous improvement. The game simulates real-world manufacturing challenges, enabling participants to experience the measurable benefits of applying SMED techniques by improving setup times, enhancing team collaboration, and optimizing process flows. In a novel extension, the game incorporates a machine learning (ML) component where students are provided with a dataset of images pre-classified as “good” and “bad” setups. Participants train an ML model to classify setups, leveraging technology to identify potential inefficiencies and errors in simulated environments. This addition bridges lean manufacturing principles with modern automation tools, providing hands-on experience in data-driven decision-making and showcasing the complementary roles of human ingenuity and machine intelligence. Through an analysis of teaching methods, and game-based learning, the study evaluates the game's effectiveness in enhancing students’ comprehension and practical application of lean manufacturing principles. By integrating this human-centric, interactive educational tool into lean manufacturing training programs, this research contributes to advancing both academic and practical knowledge in flexible automation and intelligent manufacturing. It advocates for game-based learning and ML as key strategies to meet the demands of the future of automation and manufacturing.