Data Science, Digital Maintenance. R&D, Web App, Cloud.
Alstom. United Kingdom
Data Science for digital maintenance: data processing, visualisation and reporting system. This research and development project focused on creating an innovative web-based application designed to transform how maintenance data for train fleets is managed, analysed and communicated. The platform leverages cloud storage to handle large-scale datasets and applies advanced data science techniques to process this information efficiently, generating key performance indicators (KPIs) and clear visual insights for operators and maintenance teams.
Web application for fleet insights and performance monitoring
Through smart data processing and intuitive dashboards, this system enables railway operators to track the health and performance of their rolling stock in real time. By converting complex maintenance records into accessible charts and reports, the tool supports better decision-making, proactive maintenance scheduling and optimised resource allocation, all aimed at increasing fleet reliability and operational efficiency.
Leadership from idea to customer delivery
Danilo played an instrumental role in this project’s success, providing end-to-end leadership from initial concept development and technical design to supervising the build, overseeing deployment, and managing customer handover and ongoing client relations. The project showcases how applied data science and user-friendly digital tools can deliver actionable insights and measurable value for the railway industry.
