@article {10.3844/jastsp.2025.34.39,
article_type = {journal},
title = {Error Identification and Mitigation Analysis Method Using HFACS on VR HMD},
author = {Thomas, Nkingo June and Su, Yan},
volume = {9},
year = {2025},
month = {Nov},
pages = {34-39},
doi = {10.3844/jastsp.2025.34.39},
url = {https://thescipub.com/abstract/jastsp.2025.34.39},
abstract = {Human error has long been recognized as a key factor influencing safety, performance, and efficiency in complex tasks, including those involving advanced technologies. In the context of Virtual Reality (VR) Head-Mounted Displays (HMDs), which are increasingly applied in fields such as aviation maintenance, the presence of human errors can compromise both user experience and operational reliability. This paper presents a comprehensive method for error identification and mitigation by integrating the Human Factors Analysis and Classification System (HFACS) with VR HMD technology. Focusing on the air conditioning maintenance task of the A320 aircraft, a sample of 25 maintenance personnel participated in VR based training sessions. Quantitative metrics, including error reduction rates and task completion times, were collected across multiple attempts. Initial mean completion time was approximately 10 minutes, and by the second attempt, all participants completed the maintenance in under 10 minutes (p},
journal = {Journal of Aircraft and Spacecraft Technology},
publisher = {Science Publications}
}