A Survey on Extended Reality Technologies for Industrial Maintenance

Abstract: Industrial maintenance increasingly relies on extended reality (XR) technologies, yet comprehensive analysis comparing AR, VR, and MR implementations with human-centric evaluation remains limited. This systematic literature review employs the PRISMA methodology to analyze 95 primary studies (2014–2025) that investigate implementation patterns, benefits, challenges, and evaluation criteria across XR modalities. AR dominates operational guidance (71.6%), VR prevails in training (38.9%), and MR enables collaborative maintenance (6.3%). Temporal analysis reveals three evolutionary phases: basic visualization (2014–2017), cognitive enhancement (2018–2021), and AI-integrated adaptive systems (2022–2025), mirroring the transition from Maintenance 4.0 to 5.0. Demonstrated benefits include 38% task completion time reductions and 92.4% error decreases. Human-centric factors appear in 44.2% of studies overall, with temporal analysis showing a progressive increase from approximately 25% in 2014–2017 to 58% in 2022–2025, substantiating a paradigm shift toward prioritizing cognitive support and user experience. Two novel frameworks advance theoretical understanding: an Evaluation Framework that ex-presses effectiveness as a function of technology, task complexity, and human factors; and a Technology-Task-Context Alignment Model that prescribes optimal XR-maintenance pairings. Critical gaps include the need for longitudinal field studies, standardized evaluation protocols, and economic analyses.

Mouad Danane, Abdelmajid El Ouadi and Youssef Rochdi. “A Survey on Extended Reality Technologies for Industrial Maintenance”. International Journal of Advanced Computer Science and Applications (IJACSA) 17.4 (2026). http://dx.doi.org/10.14569/IJACSA.2026.0170479

@article{Danane2026,
title = {A Survey on Extended Reality Technologies for Industrial Maintenance},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2026.0170479},
url = {http://dx.doi.org/10.14569/IJACSA.2026.0170479},
year = {2026},
publisher = {The Science and Information Organization},
volume = {17},
number = {4},
author = {Mouad Danane and Abdelmajid El Ouadi and Youssef Rochdi}
}