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Trenitalia’s IoT Strategy Makes the Trains Run on Time

Feature Article | September 29, 2016 by Judith Magyar

Italy’s leading train company is setting the pace when it comes to predictive maintenance.

Who likes waiting for trains? No one, that’s who.

Trenitalia is working with SAP to prove there’s a smarter way to keep trains in top shape

One reason for late trains is that when transportation companies need to take care of unplanned maintenance, it cost more time, labor and ultimately money. Traditionally, operators look at how many months the train has been in use or miles traveled to estimate the need for mechanical attention; and overlook more important factors like equipment stress and weather conditions.

Trenitalia is working with SAP IoT to prove there’s a smarter way to keep trains in top shape that’s more efficient – and pays off big in operating savings and happier customers.

“One of the most expensive and critical processes for a railway company is rolling stock maintenance,” says Danilo Gismondi, CIO Trenitalia, Italy’s leading train company and a member of the FS Group, Europe’s most profitable railway player.

“At Trenitalia we’ve managed to improve it by analyzing data coming from thousands of sensors installed on our trains. The Dynamic Management Maintenance System (DMMS), built on a SAP HANA platform, can predict failures before they actually happen.”

Transforming the Maintenance Mix

Traditionally, maintenance schedules are based on a corrective/preventive system. Unfortunately fixed schedules that are based on distance and time have low correlation with the wear of components such as brakes, wheels, doors, and engines. The problem with this approach is that it does not capture the real condition of each component, which can vary based on factors such as the kind of service offered by the vehicle, number of rides per day, environmental conditions and occupancy levels.

All that changes with DMMS. Now, Trenitalia can link data from equipment such as motors, batteries and brakes with lifecycle models, usage wear and other performance indicators.  This enables the company to precisely predict the wear of a part by factoring in parameters such as cycles, hours of operation, kilometers, temperature, and so on. Maintenance occurs when predefined thresholds are reached, or when a specific  parameter goes out of the normal range, meaning a failure could be imminent and must be corrected immediately.

Switching Tracks has Advantages

According to Danilo, DMMS is going to mean big changes. Switching from a corrective/preventive system to a predictive one means maintenance activities will be performed differently. In addition, the use of tools like scanners and robots to detect faults, and the introduction of tablet devices to manage the maintenance program will also  speed up the digitalization of maintenance activities.

Another important innovation is the introduction of an integrated communications system among suppliers, engineers, technicians, and external partners to replace the current haphazard system. This will enable everyone to share information and take advantage of each other’s skills and best practices.

Last, but certainly not least, the new system will lead to costs savings in at least three areas: the number of maintenance operations, the duration of each operation, and number of parts replaced.

Today, September 29, SAP and Trenitalia are holding a customer showcase in Rome and Naples Italy, riding on one of Trenitalia’s high-speed trains. Speakers from both companies include SAP CEO Bill McDermott, Executive Board Member Bernd Leukert and Trenitalia CEO Barbara Morgante.  Follow the event on Twitter at #SAPIoT.

 

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