Discipline: Computer Sciences and Information Management
Subcategory: Computer Science & Information Systems
Session: 3
Room: Hoover
Shayra L. Santiago-Borges - Virginia State University
3D modeling and Virtual Reality (VR) are very useful tools in the Digital Manufacturing Process for workplace training and development purposes. With VR environments within the industry, it will help companies achieve rapid understanding of manufacturing processes and decision-making by visualizations and VR experiences. The importance of this research is to advance digital manufacturing for the next generation and help companies improve their manufacturing processes. Within this research, it is conducted using Unity 3D simulation software environment, C Sharp, VR, modeling, designing, and interactive programming. Unity is a game development platform with C Sharp coding that is used to build high-quality 3D and 2D games across desktop, mobile, gaming consoles, and VR or Augmented Reality (AR). The results of our project will have software demonstrative environment of different machines in the manufacturing process. These environments will simulate or emulate the operation of a 3D Printer to be able to understand how they work. The created virtual machine will have a virtual interactive user interface that will be accessed through the VR headset Meta 2 and/or Oculus. This will allow the users to experience the machines in first person and improve their handling of the machines in their workplace. To conclude our research, we will be successful to demonstrate the virtual environment that has been created using Unity. This will allow for a simulated realistic machine environment for further development of digital manufacturing and workforce training. References: Choi, S., Jung, K., & Noh, S. D. (2015). Virtual reality applications in manufacturing industries: Past research, present findings, and future directions. Concurrent Engineering, 23(1), 40?63. doi: 10.1177/1063293×14568814.
Funder Acknowledgement(s): This material is based upon work supported by the National Science Foundation under Grant No. 1818655. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
Faculty Advisor: Dr. Ju Wang, jwang@vsu.edu
Role: I did modeling, coding, testing, evaluating, writing abstract and anything else with the help of my mentor.