Digital monitoring and predictive diagnostics technologies as a tool for rolling stock lifecycle management

Aim: to evaluate the impact of digital monitoring and predictive diagnostics technologies on the management of railway rolling stock life cycles. Materials and Methods: the study is based on a comparative analysis and systematization of international and Russian standards, industry regulations, and scientific publications on asset life cycle management, as well as the implementation of digital projects in the field of monitoring and predictive diagnostics technologies in railway transport. Results: the article systematizes methodological approaches to asset lifecycle management and assesses the state of the railway industry's regulatory framework in this area, specifics of using a predictive approach in managing the lifecycle of rolling stock as well. The paper clarifies the impact of digital monitoring technologies and predictive analytics on lifecycle management and identifies key drivers of effects. The paper also highlights the benefits of creating a trusted information exchange environment for various stakeholders involved in the lifecycle of freight cars. Conclusion: the research findings will enable an assessment of how monitoring technologies and predictive analytics impact railway rolling stock lifecycle management. These results will prove valuable for planning and implementing digital transformation projects in this field, as well as for conducting further scientific research and developing industry-specific regulatory documentation.