An Experiential Learning Approach to Industrial IoT Implementation of Smart Manufacturing through Coursework and University-Industry Partnerships

Abstract

As the Internet of Things (IoT) and artificial intelligence (AI) continue to reshape the industrial landscape, the US manufacturing sector faces pressing challenges in bridging the skills gap. This issue is not merely about filling vacancies but adapting to the de-mands of AI-centric manufacturing roles. Traditional engineering curricula often lag behind in catering to the requirements of contemporary AI and IoT paradigms. Recognizing this shortfall, Purdue University, in part-nership with local industries, launched an innovative graduate course. This initiative is crafted to equip engineering graduate students with a comprehensive grasp of data, from IoT sensor and machine connectivity to its interpretation through AI-driven analytics. An in-tegral part of the course was the lab sessions, structured around hands-on activities. Through these labs, students had the opportunity to immerse in IoT and AI-related technologies, gaining practical experience and insights. Building on the knowledge acquired in the lectures and labs, students performed on semester-term projects in collaboration with regional manufacturing compa-nies. Beyond academic advancement, the course offers a unique opportunity for regional firms to harness the transformative potential of IoT and AI, helping them navigate through their operational challenges. This study delves into the course’s pioneering design, rooted in the experiential learning theory (ELT), highlighting the significant outcomes and showcasing the collaborative projects that seamlessly integrated classroom learning with practical, real-world applications.