ORCID Identifier(s)


Graduation Semester and Year




Document Type


Degree Name

Master of Science in Industrial Engineering


Industrial and Manufacturing Systems Engineering

First Advisor

Deb Shuchisnigdha


The recent advancement of additive manufacturing (AM) technologies leads to an extensive need for an industrial workforce. Training in AM requires expensive capital investment to install and maintain this technology and proper knowledge about potential safety hazards. Experiential, immersive training platforms like Virtual Reality (VR) can overcome this challenge by providing opportunities for effective learning in a safe and controlled environment. VR can teach students through active participation and immersive, hands-on experiences, which is especially important for manufacturing processes involving high-risk conditions. VR can expose students to manufacturing hazards and allow them to learn through trial and error without causing any damage to real-world resources. Acknowledging the benefits of VR, two studies were developed that explore the development and evaluation of a virtual training platform for AM, explicitly focusing on selective laser sintering (SLS) printing. The platform leverages VR technology to provide undergraduate and graduate engineering students with a safe and immersive learning environment. The study begins with an in-depth literature review, examining the benefits of experiential learning and the potential of VR for enhancing engineering education. It also investigates the challenges and safety considerations associated with AM processes. Building upon this foundation, comprehensive research studies were carried out involving student participants from the Decision Analysis in the Systems Design course and the Safety Engineering course at the University of Texas at Arlington to evaluate the effectiveness of the virtual training platform. The virtual environment of the studies contains a selective laser sintering printer, a workstation with necessary supplies and safety equipment, a control panel, and information panels for process planning and hazard identification. The training platforms provide students with significant learning opportunities to gain hands-on experience with a virtual 3D printer and critical engineering skills based on operating process parameters and safety measures. The study utilizes eye metrics analysis, subjective surveys, and performance metrics to assess students' attention, engagement, learning outcomes, and satisfaction. Time-series data on eye movement and controller-based interactions, demographic information, and experience survey responses are collected. Gaze behavior analysis and subjective responses provided helpful insights into the challenges encountered by students, guiding future researchers in improving the platform's instructional design and providing assistive instructions. The outcomes of this research have practical implications for academia and industry, facilitating the training of a competent workforce capable of leveraging AM technologies. By providing a detailed exploration of the virtual training platform's development and evaluation, this study contributes to the advancement of experiential education through virtual reality.


Additive manufacturing, Virtual reality, Virtual training, Student attention, Eye tracking, Safety engineering


Engineering | Operations Research, Systems Engineering and Industrial Engineering


Degree granted by The University of Texas at Arlington

Available for download on Thursday, August 01, 2024