Augmented Reality System for Training of Heavy Equipment Operators in Surface Mining

Autor: Valencia Quiceno, Juan David, Kecojevic, Vladislav, McBrayer, Amy, Bogunovic, Dragan
Zdroj: Mining, Metallurgy & Exploration; 20240101, Issue: Preprints p1-13, 13p
Abstrakt: United States federal laws mandate that mining companies ensure a safe workplace, implement approved training programs, and promptly report work-related injuries. The mining industry’s commitment to innovation reflects a history of adopting technological advancements to enhance environmental sustainability, workplace safety, and vocational training. The objective of this research was to develop an augmented reality (AR) system for heavy equipment operators (HEOs) in surface mining. The developed system has the potential to enhance mine safety, training, and data-driven decision-making, which presents a significant step toward a more sustainable, effective, and technologically driven mining training, contributing to the industry’s evolution and growth. The AR Training System leverages Microsoft’s Power Platform and HoloLens 2 capacities to provide operators with detailed, immersive training guides for three mining equipment including bulldozers, motor graders, and end dump trucks. These AR guides combine 3D objects, informative images, and videos to enhance learning and safety. The system also provides an efficient approach to data collection during HEO training, having the potential to modify the training guides based on user performance. The system was developed and applied via a case study in a surface mine in the southern United States.
Databáze: Supplemental Index