SBIR Phase I: Virtual and Augmented Reality Enabled Personalized Manufacturing Training

This SBIR Phase I project will research the feasibility of applying virtual reality (VR) and augmented reality (AR) technologies in manufacturing and material testing training programs to increase academic achievement, accelerate progress toward degree and foster more effective use of expensive lab-equipment. According to 2014 statistics, in the United States, less than 40% of students entering college in STEM fields finish with a STEM degree. And even for those who finish, a majority (over 60% ) take several years longer than the nominal time of 4 years. Providing students with VR and AR enabled personalized manufacturing labs is a promising way to increase students' engagement and better prepare them for future careers as well as broaden students' outlook on innovation. As described in the recent US council report on competitiveness, advanced manufacturing has the largest multiplier effect on jobs. In order for the US to gain competitiveness in this sector, there is a pressing need for a trained workforce that is able to develop new materials testing protocols and manufacturing processes. This SBIR project aims to develop technologies that enable the education sector to leverage VR and AR to accelerate training. Proposed software will be evaluated through pilot testing. Technology and insights resulting from this project may find applications in other domains such as life sciences. Key technical innovations in this proposed research include the development of a novel high-fidelity modular virtual object model, customized task models based on evidence centered design, and methods to flexibly combine object models with task models to rapidly develop activities suitable for virtual reality (VR) and augmented reality (AR) devices. These innovations may significantly reduce the content creation cost and potentially dissolve the boundary between classroom education and hands-on training, providing an effective and seamless educational experience. In the long term, these innovations may also be applied broadly to training in other domains. The overarching goal of this SBIR project is to evaluate the feasibility of the proposed system for content creation and learning analytics and apply them to create innovative content for use in manufacturing courses. The proposed system and content will be evaluated via pilot testing with engineering students to collect rich datasets comprising videos, sensor time series data and simulation-event logs. Data analysis will seek evidence for changes in both students outcomes (changes in content knowledge, engagement, attitude towards engineering, self-efficacy towards learning engineering, usability of the product) and instructor outcomes (attitudes about the usefulness of the product).