SAP and Trenitalia’s IoT-Enabled Dynamic Maintenance

Earlier this year, SAP and Trenitalia organized an Executive Summit in Rome and the National Railway Museum in Pietrarsa (Naples).  During the event Trenitalia, Italy’s national railway operator, communicated the company’s new IoT-enabled approach to maintenance management that will run on SAP software.  Trenitalia expects that the approach will help it save more than €100 million annually in maintenance costs.

SAP discussed the partnership and co-development with Trenitalia and the company’s commitment to investing in IoT; and announced SAP IoT Solutions and Industry 4.0 Solution Package, acquisitions of two companies, and the creation of SAP IoT Labs.

The combined announcements, the presence of both companies’ CEOs, plus the CEO of Trenitalia’s mother company Ferrovie Dello Stato Italiane, and the prestigious locations, indicated the high importance of the event for both companies.

Key takeaways are:

• SAP is making a major commitment to Industrial IoT


• Trenitalia is pushing the boundaries to become a highly competitive international railway service provider


• Digital transformation and culture change are inseparable

This report builds upon an earlier blog, providing more details about:

• Trenitalia’s motivation


• The condition monitoring and expert systems currently in place


• The goals, design process and early steps of a predictive maintenance system in SAP


• Anticipated benefits, and


• Recommendations organizational aspects related to digital transformation.

For an analysis of SAP’s announcements please refer to Greg Gorbach’s blog.

Trenitalia’s Challenges and Motivations

Trenitalia, Italy’s state-owned, public railway company with a €5.5 billion turnover, is the train operation branch of Ferrovie Dello Stato Italiane.  One of the key triggers for transformation to IIoT-enabled predictive maintenance, according to Paolo Masini, Rolling Stock Engineering Director at Trenitalia, is the competition on the high-speed market on the same tracks.  In addition, the approach aims to increase the company’s competitiveness, because tenders for regional and national services are opening for international players.  Trenitalia would also like to bid with services on international markets.  The company aims to be highly competitive based on both cost and perceived client value such as safe, sustainable and comfortable travel, with minimal delays and breakdowns.

The company aims to be better than others and wants to be “on target on time,” said Trenitalia’s CEO Barbara Morgante.  “On time” also refers to the timeliness of a given quality of service to an appropriate price, which is more ambitious and specific than just reduce “time-to-market.”  The company is investigating additional ways to improve the travel experience by extending the scope of travel from station-to-station to a door-to-door experience, providing similar comfort as travelling by car, explained Mr. Renato Mazzoncini, CEO of Ferrovie dello Stato Italiane. Client service quality is also a high priority for Trenitalia, and this includes reliability and punctuality.  Therefore maintenance is not only a cost saving opportunity but also contributes to quality and satisfaction.

Corrective and Preventive Maintenance Less Effective

Trains run in climate conditions that range from Alpine to Mediterranean.   Some trains travel short distances with a lot of braking and acceleration, and opening and closing cycles of doors; others travel large distances and make more wheel rotations.   In addition, trains experience uneven wear on right or left wheels depending on the direction they lean, causing unsymmetrical wheel accelerations. Classical mileage-based preventive maintenance is therefore not very effective, since too many inspections don’t find anything wrong, but still do not prevent breakdowns.  As maintenance represents the company’s largest expense, it was critical to investigate more efficient approaches to maintenance.

In our next blog in this series we report about the IIoT-enabled Maintenance approaches used in Trenitalia and the road towards predictive maintenance. Check back on January 13th for part two in this three part series.