The necessary prerequisite for this is provided by sensors fitted to vehicles and infrastructure that measure the stress on components and provide information about their current condition. The basic idea is that instead of replacing components rigidly according to specified manufacturer deadlines or in-house maintenance concepts, they are replaced precisely when they need to be.
Markus Krippner, division manager at TUV Rheinland InterTraffic, said: "Rail vehicles and the infrastructure in rail traffic are highly complex systems with immense maintenance and repair costs. It is therefore all the more important for operators that both regular service and the necessary repairs run efficiently and cause as little downtime as possible. Technical interruptions should not occur at all, if possible."
With condition-based, sensor-supported maintenance concepts, TUV Rheinland brings the requirements of rail transport down to a common denominator: companies can respond flexibly to maintenance needs and perform scheduling efficiently. In addition, continuous monitoring allows technical faults to be detected at an early stage, short-term failures to be reduced and the availability of the fleet to be increased. This results in another effect of condition-based maintenance, from which rail transport companies also benefit: improved punctuality and fewer breakdowns due to technical faults that increase customer satisfaction.
"We have a high level of technical expertise in condition monitoring of critical components in rolling stock and infrastructure. Now we are taking the logical next step translating the measurement data into efficient, flexible and cost-saving maintenance concepts for our customers," Krippner continued. "Continuous monitoring makes it possible to use components in a targeted and safe manner until they reach their maintenance limit."
The modular approach of CBM enables rail transport companies to compile all TUV Rheinland services in the maintenance value chain according to specific requirements and needs. This starts with feasibility studies on a possible CBM introduction and extends to condition monitoring including storage, wireless transmission of data, and visualisation of results in automatically generated reports or dashboards.