TITLE:
Discussion on the Current Status and Strategy Optimization of Intelligent Operation and Maintenance for Urban Rail Transit Vehicles
AUTHORS:
Xueling Wang
KEYWORDS:
Urban Rail Transit, Vehicle Operation and Maintenance, Prognostics and Health Management (PHM), Condition-Based Maintenance, Strategy Optimization, Life Cycle Cost (LCC)
JOURNAL NAME:
Open Journal of Applied Sciences,
Vol.15 No.12,
December
29,
2025
ABSTRACT: With the rapid expansion of the networked operation scale of China’s urban rail transit, the number of vehicles has increased exponentially. The traditional operation and maintenance (O&M) model, which mainly relies on “scheduled maintenance” supplemented by post-event “corrective maintenance”, is confronted with prominent challenges in terms of maintenance efficiency enhancement, life cycle cost (LCC) control, and operational reliability guarantee. As the core driver for the transformation and upgrading of the urban rail transit industry, intelligent O&M leverages the Internet of Things (IoT), big data, and artificial intelligence technologies to offer a novel solution to address these contradictions. This paper systematically reviews the application status of Prognostics and Health Management (PHM), intelligent inspection equipment, and physical reliability analysis in urban rail transit vehicles. It conducts an in-depth analysis of the primary contradiction in the current O&M system. The structural mismatch between advanced intelligent technologies and lagging management models. It further examines issues such as the absence of quantitative evaluation standards and insufficient integration of data-driven approaches with physical mechanisms. In response to these pain points, the paper proposes maintenance strategies based on Life Cycle Cost (LCC) management, a PHM architecture driven by both mechanisms and data, and an intelligent efficacy evaluation and dynamic decision-making mechanism. The objective is to promote the transformation of urban rail transit vehicle O&M from “passive execution” to “active decision-making” through the in-depth integration of technology and management, thereby providing a theoretical basis and practical reference for the high-quality development of the industry.