In the rapidly evolving world of urban rail transit, where systems are growing increasingly complex, a groundbreaking solution has emerged from CRRC Corporation Limited (CRRC). The company has unveiled the Aizor (Zhuolun) Large Model, an artificial intelligence (AI) solution that integrates the entire manufacturing chain in the rail transit field. This innovation is poised to revolutionize operation and maintenance (O&M) practices, offering a glimpse into the future of efficient, safe, and cost-effective rail transit systems.
At the heart of this transformation is the “CRRC Intelligent Operation and Maintenance Platform for Urban Rail Transit,” constructed around the Aizor Large Model. The platform’s “12436” framework, as detailed in a recent study published in *Kongzhi Yu Xinxi Jishu* (translated as *Control and Information Technology*), includes 1 intelligent O&M solution package for urban rail vehicles, 2 data centers, 4 application systems, 3 enabling technologies, and 6 simplification and unification principles. This comprehensive approach aims to address the pressing needs of modern rail transit operations.
Lead author Cui Tingqiong, whose affiliation is not specified, highlights the innovative practices of the platform, particularly in multi-source heterogeneous data fusion, AI large model-empowered fault diagnosis, predictive maintenance, and O&M cost optimization. “The platform drives a paradigm shift from ‘planned maintenance’ to ‘condition-based maintenance’ and ‘predictive maintenance,'” Cui explains. This shift is supported by scenario-based large models including “Yuzhi” and “Yujian,” which are designed to enhance the efficiency and accuracy of maintenance operations.
The implications for the energy sector are significant. As rail transit systems expand, the demand for energy-efficient and reliable operations grows. The CRRC Intelligent Operation and Maintenance Platform offers a solution that not only reduces maintenance costs but also ensures the safety and longevity of rail transit systems. By leveraging AI and large models, the platform can predict potential issues before they arise, minimizing downtime and maximizing operational efficiency.
“This study summarizes a replicable and transferable CRRC solution for building intelligent O&M systems in the rail transit industry,” Cui notes. The platform’s ability to integrate various data sources and apply advanced AI techniques sets a new standard for the industry. As urban rail transit systems continue to grow, the adoption of such intelligent platforms could become a norm, driving cost reduction, efficiency improvement, and safety assurance.
The research published in *Kongzhi Yu Xinxi Jishu* provides a roadmap for the future of rail transit maintenance. By embracing AI and large models, the industry can achieve unprecedented levels of efficiency and reliability. The CRRC Intelligent Operation and Maintenance Platform is not just a technological advancement; it is a testament to the power of innovation in shaping the future of urban rail transit.