Big data analytics in support of the under-rail maintenance management at Vitoria - Minas Railway

This paper describes an ongoing study using data collected by an instrumented ore car on Vitoria-Minas Railway, operated by Vale in Brazil. The research uses big data analysis methods over collected data by the instrumented car during its voyages. Railway geometry issues can cause undesirable movements on the wagons that can cause discomfort for passengers or instability for the cargo. In the worst scenario, derailments can occur. Each second, several sensors installed on the instrumented car collect data about velocity, acceleration, and movements on the wagon. The volume of collected data is impressive since the railway has about 2,000 km of extension. That volume compels us to use big data analytics methods. As the result of the research, the team aims to establish some levels of operational conditions, named as severity indexes, which can indicate to the maintenance teams the necessity of intervention on the railway.

Automated summary

This paper describes an ongoing study that uses data collected by an instrumented ore car on Vitoria-Minas Railway in Brazil, operated by Vale. The research applies big data analysis methods to analyze railway geometry issues and establish severity indexes for maintenance intervention.