How Predge’s predictive maintenance solutions kept Sweden’s steel shuttle on track

Swedish company Predge helps railway companies make the shift from reactive to predictive maintenance activities through modular software-as-a-service solutions (SaaS). RailTech.com spoke to Predge CEO Simo Pykälistö about the company’s services and one of its recent projects.

Predge has its roots in the academia and was founded in 2013. While a SaaS company, it does not want its decision support services for operation and maintenance to be “just another screen” for the client to look at, as Simo puts it.

“We predict when damage might occur or what the remaining useful life of an asset is. This allows clients to better schedule and plan maintenance activities. Once you can do this based on information, it also allows customers to better align maintenance need with maintenance capacity”, Simo explains. Some of the analytics features include wheel damage prediction, bearing failure prediction and on-route load shifting.

Predge, according to Simo, has an agnostic view to data, in that it utilises and integrates data from any available source, as long as it makes sense analytically. It also has a hybrid modelling approach that uses machine learning and artificial intelligence (AI) on the one hand, but also its own knowledge regarding the physics of failure and domain knowledge on the other.

Of course, predictive maintenance solutions are not new. So what is it about Predge’s services that set them apart? According to Simo, it is the hybrid-modelling approach first and foremost, which combines purely data-driven tools with demand knowledge for better results. It also happens in close cooperation with customers, to better understand who is best served with what information.

The company’s solutions are modular, so that the customer can choose different features that address various needs. This enables the client to pick the low-hanging fruit, and it also make it easy to quickly benefit from the service.

Steel shuttle challenges

One such group of customers are the companies involved in the so-called steel shuttle. This is a freight train that transports steel slabs weighing 2,000 tonnes each from producer SSAB’s Luleå-based production site to Borlänge over a distance of 1,200 kilometres. Three 20-car trains run in each direction over the course of 24 hours.

“The steel shuttle faced a number of challenges due to frequent unwanted stops as a result of wheel damage. This not only reduced availability on the line, but also resulted in elevated operational and maintenance costs. This, then, put a strain on workshop capacity and resources” Simo says.

In the first year already, the number of stoppages on track due to wheel damage was reduced by 75 percent using Predge’s tools. Furthermore, 95 percent of damage was predicted with the 1,200-3,600 kilometre-range.

“This meant that maintenance could be planned more efficiently. Had maintenance capacity been bigger, we would actually have scored a better reduction figure than the mentioned 75 percent”, Simo explains, adding that the companies involved now have much better understanding of how long a wagon can remain in use. And when a wagon does come to maintenance, the teams at the terminal stations now know which wheel to tackle. “Maintenance along the tracks, out in the cold, is almost a thing of the past.”

The steel shuttle is used to transport specialised slabs of steel. Image: SSAB

Added benefits

Finally, the information regarding predictive maintenance does not benefit one single company. In fact, it has a snowballing benefit. “Steel producer SSAB benefits from smooth transportation, as does freight train operator Green Cargo. Meanwhile wagon owner VTG and maintenance services firms Euromaint, SweMaint and Duroc are in a position to more efficiently plan their work, while transport administrator Trafikverket can be pleased that faulty wheels are now not damaging the infrastructure as frequently as they did”, Simo concludes.

Predge has solutions for three product families: rolling stock, rail infrastructure and conveyors. These solutions are built on existing data, which for rolling stock means condition data from available wayside detectors, onboard systems, inspections, and other sources such as maintenance systems, production systems, etc.

Want to learn more about Predge and its solutions? Come and meet them at RailTech Europe this month. Click here for more information and registration. 

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Author: Nick Augusteijn

Editor RailTech.com

1 comment op “How Predge’s predictive maintenance solutions kept Sweden’s steel shuttle on track”

bönström bönström|07.06.22|12:14

However, regardless, if maintenance is “optimised”, by sophisticated data, etc, for claiming optimal the track shall prove safely calculable, thus providing for serious safety factors, as otherwise at any public assets!
(Regrettably current “state of the art” tracks were not designed for todays traffic, for todays demand! (Majority of ware owners, neither can not afford luxury of not bothering about risks by delayed supplies.) A shift, a New Old Railway” now is needed!

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