Affordable virtual and augmented reality training modules for workforce development and smart manufacturing
In the face of rapid technological advances, including digital, additive, and smart manufacturing, it is essential to continually update manufacturing competency to facilitate skilled workforce development. This study explains a user-friendly Virtual Reality/Augmented Reality/ (VR/AR) training framework for training manufacturing processes. Process equipment and operational protocols are complex and demand for highly skilled and trained operators. Operators trained using the current methods, including in-class and computer-based training, continue to need help with some of the key process equipment operations, causing batch failures resulting in significant loss of time and money. Conventional avenues and traditional computer-based training have been routinely employed to educate operators. However, VR/AR-based process training will remedy the exposed inadequacies of smart manufacturing training processes that are causing continued operator errors. The virtual simulation offers coordinated visual and proprioceptive (spatial perception) feedback cues to develop motor skills for procedural knowledge and memory. The interactive training explores the relationships between actions and outcomes to promote schema building and strengthen trainees' mental models in manufacturing operations. This project has a significant commercial impact within the manufacturing industry owing to increased operational efficiency, reduced product delivery time, and increased accuracy. Optimal training aids affordable, precise, and quality product delivery for generic and personalized medicines to needy patients, thus resulting in a significant societal impact. It will positively impact the professional development of trainees and operators through training in cutting-edge research, innovation and entrepreneurship.
Authors
- Magesh Chandramouli (ORCID: https://orcid.org/0000-0002-3500-0946)
- Ashayla Williams (ORCID: https://orcid.org/0009-0000-4908-2930)
Institutions
- Purdue University West Lafayette (US)
Publication Details
- Journal
- Journal of Manufacturing Engineering
- Published
- 2024-12-01
- DOI
- https://doi.org/10.37255/jme.v19i4pp101-107
- Citations
- 1
- Primary Topic
- Digital Transformation in Industry
- Type
- article
- Field-Weighted Citation Impact
- 0.35