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This study explores factors promoting and inhibiting advanced technology adoption in small- and medium-sized manufacturing firms (SMEs). With AI’s rapid advancement impacting productivity and efficiency across industries, understanding the challenges that SMEs face to remain competitive is crucial. Utilizing the Unified Theory of Acceptance and Use of Technology (UTAUT) model as a theoretical framework, we analyzed managers, engineers, and line workers’ observations on workforce challenges, training needs, and opportunities faced by SMEs to provide insights into their smart manufacturing deployment experiences. Our findings highlight social influence’s role in promoting technology adoption, emphasizing community, shared experiences, and collaborative networks. Conversely, effort expectancy emerged as the largest inhibitor, with concerns about the complexity, time, and resources required for implementation. Individuals were also influenced by factors of facilitating conditions (organizational buy-in, infrastructure, etc.) and performance expectancy on their propensity to adopt advanced technology. By fostering positive organizational environments and communities that share success stories and challenges, we suggest this can mitigate the perceived effort expected to implement new technology. In turn, SMEs can better leverage AI and other advanced technologies to maintain global competitiveness. The research contributes to understanding technology adoption dynamics in manufacturing, providing a foundation for future workforce development and policy initiatives. 

The significance of practical experience and visualization in the fluid power discipline, highly tied to students’ success, requires integrating immersive pedagogical tools for enhanced course delivery, offering real-life industry simulation. This study investigates the impact of using virtual reality (VR) technology as an instructional tool on the learning and engagement of 48 mechanical engineering technology (MET) students registered in the MET: 230 Fluid Power course at Purdue University. An interactive VR module on hydraulic grippers was developed utilizing the constructivist learning theory for MET: 230 labs, enabling MET students to explore light- and heavy-duty gripper designs and operation through assembly, disassembly, and testing in a virtual construction environment. A survey consisting of a Likert scale and short-answer questions was designed based on the study’s objective to evaluate the students’ engagement and perceived attitude toward the module. Statistical and natural language processing (NLP) analyses were conducted on the students’ responses. The statistical analysis results revealed that 97% of the students expressed increased excitement, over 90% reported higher engagement, and 87% found the VR lab realistic and practical. The NLP analysis highlighted positive themes such as “engagement”, “valuable experience”, “hands-on learning”, and “understanding”, with over 80% of students endorsing these sentiments. These findings will contribute to future efforts aimed at improving fluid power learning through immersive digital reality technologies, while also exploring alternative approaches for individuals encountering challenges with such technologies.