Originally published in a Linkedin blogpost. The press release can be found here.

The rail transportation sector across the world is at a unique juncture. On one hand, it is being increasingly acknowledged as the most eco-friendly transportation mode for its active role in decreasing emissions. On the other hand, constant breakdowns of rail services due to aging infrastructure and unsynchronized maintenance planning has led to some questioning its efficiency.

However, in the age of industrial revolution 4.0 there is an opportunity to move over to predictive maintenance strategies by considering both the vehicle and the track as a single system. Especially considering that the traffic patterns on a railway line for a given period is more homogeneous as compared to a roadway. This factor coupled along with powerful computing interfaces, there lies an opportunity to 'game' the vehicle-track interaction to predict maintenance intervals and grade existing vehicle classes to further encourage innovation in the way we design vehicles.

in the age of industrial revolution 4.0 there is an opportunity to move over to predictive maintenance strategies by considering both vehicle and track as a single system.

With increasing role of advanced simulation tools across all engineering domains, industrial standards in railways today even have provisions to use simulations to certify vehicles w.r.t their safety and comfort requirements. In this context, Digital-twin based methods are increasingly gaining prominence in applications such as condition monitoring, derailment prevention, maintenance scheduling, etc. Leveraging these developments, along with researchers at KTH I have been working in Shift2Rail projects to construct a system-wide model to describe how vehicles and track interact with each other and deteriorate over a long period. The approach has been multi-disciplinary encompassing various domains such as vehicle dynamics, contact mechanics, track maintenance strategies, econometrics, etc. Constructing a digital twin of the vehicle-track system can help plan maintenance, enhance safety and further improve the underlying sub-systems.

a system-wide model to describe how vehicles and track interact with each other and deteriorate over a long period

As an example for the application of Track-friendless 4.0, we checked the evolution of rail surface damage for two different vehicle designs over a long tonnage period also accounting for maintenance interventions in the form of rail grinding. The time-lapse video below demonstrates rail wear depth evolution and risk for the formation of cracks accumulated over tonnage.

Video: Rail profile deterioration compared for two different bogie models

From the TRAVisions brochure:

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