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Predictive maintenance for Dutch rail

Prorail

Engineers in the Netherlands have improved rail reliability by taking a new, predictive approach to track maintenance.

In 2009 rail maintenance in the Netherlands took its first steps towards a radical transformation when it moved from being a descriptive to a predictive maintenance regime.

This seemingly simple switch has involved a complete overhaul of the processes, mindsets and the contracts used to carry out maintenance.

The company behind the move is Asset Rail, a joint venture between Arcadis and Dutch contractor Dura Vermeer.

Successful approach

At the start it had only one contract, but its approach has been so successful that it now has five and maintains 25% of the 7,000km of track on the Dutch network. Technical failures have fallen by 64% and maintenance costs are down by 40%.

Before this, the network had reached breaking point.

Repairs were being carried out according to a standard, with no real connection between the cause of a failure and the reason to maintain a piece of infrastructure. If defects were spotted, contractors had no incentive to carry out repairs immediately as it was more lucrative for them to do the work during overtime hours.

Delays, failure rates and costs mounted, and passengers became increasingly frustrated.

Prorail3

Prorail3

Using data to programme maintenance is more efficient

“The system itself was driving negative behaviours and it was more beneficial to behave in a bad way than to proactively make the situation better,” says Arcadis UK rail business partner, sector director Chris Pike.

Under the new system, contractors are incentivised to deliver an agreed level of performance.

“As part of the contract if you achieve the outcomes based on performance, then you get the reward,” says Arcadis programme manager Peter Dourlein. “If you don’t, you get paid your base cost. In a highly competitive market, profitability only comes if you deliver the performance. Strong financial incentives are key.”

At the heart of the new thinking, is the joint venture’s failure mode, effects and criticality analysis (FMECA).

It was more beneficial to behave in a bad way than proactively make the situation better

Using targeted data analytics combined with technical insights Pike says Arcadis/Dura Vermeer was able to start thinking about the failure mode and the maintenance strategies so it could identify problems “at an optimal point” before failure. Contractors can then pre-emptively carry out repairs, reducing delays and increasing passenger satisfaction.

The first step in the process says Pike, was for the team to build up a “really clear view” of the asset base and the range of components, switches, and other asset sets. Then it collected the data. The team used measurement trains, remote condition monitoring, sensors on drones and other data input sources to build up a picture of a component’s performance.

By connecting the different sets of data and using quantitative modelling, the team was able to find the underlying relationships between and dependencies of the assets, including their use and performance. He says before this regime was introduced, the network had many different smart assets, but little was being done with the data collected from them.

“First:  identify those problems and then say ‘what are those problems and what do they mean?’” says Pike. “With single data sources, it limits your ability to discern why they’re happening.

Performance-based culture

“This was the first step: to create a performance-based maintenance model with the infrastructure manager. The next step was then for the infrastructure manager to procure that across their network.

“For that we had to come up with a workable model which would have the key performance indicators needed to drive that.”

Of course, at the beginning it was not possible to prevent all failures occurring – the predictive maintenance regime had yet to kick in – and it was a case of being proactive to drive down the time to carry out repairs.

The team then brought in the second part of the transformation. A network of rapid responders incentivised to solve problems as quickly as possible.

Under the new regime, contractors are set a time period in which they have to fix a problem – 15 minutes to get to site and 60 to 70 minutes once there: a total of only 1 hour 25 mins to rectify an issue.

If you regularly tamp then you will shorten the remaining life of the track because you crush the stone under the track

To help the rapid response team, Asset Rail built a specialist control room. From here data can be analysed and useful information about how long repairs are likely to take can be passed on to contractors and the travelling public.

In another radical departure from the descriptive maintenance regime, the team took the view that some of the regular maintenance activities were actually doing more harm than good.

“So, we said ‘let’s just not do some of them’,” says Pike “It created some head space to develop the thinking and the strategy while keeping the railway running.

“Then we could start to develop and introduce strategies for some of the individual components from the data we were analysing.”

Routine work stopped

Activities such as routine track tamping  – compacting the ballast under railway sleepers to stop movement – were stopped.

“What we have stopped is the unnecessary tamping,” says Dourlein. “If you regularly tamp then you will shorten the remaining life of the track because you crush the stone under the track.

“By not doing this, it saves you money and it extends the life of the track; this is one of the most profound ones as it’s high-volume descriptive-type maintenance.”

Pike adds: “We took the view to stop doing it routinely. We will still do it, but rather than doing it based on a set of rules which says do it every six months, we will do it based on strategy.”

The data analytics used to develop the strategies have been in development within Arcadis since the 1980s, says Dourlein. The consultant has also designed its own data monitoring system which can be used remotely to alert operators to component failures. Information it gleans is then shared with ProRail, the Dutch rail operator, helping the whole network to improve. This is particularly important with safety related failures says Dourlein.

Prorail2

Prorail2

One example of where targeted improvements are made is in turn-outs, the mechanisms which allow trains to change tracks

One example of where targeted improvements are made is in turn-outs, the mechanisms which allow trains to change tracks.

“Turn-outs on the network, don’t behave in the same way, have the same functionality or the same levels of traffic,” says Pike. “It’s starting to look at those from a risk analysis point of view around which are the high and low risk ones and why.”

After carrying out risk assessments, Pike says his team can decide when and how frequently to carry out maintenance.

Despite the technical change behind the new process, changing mindsets has been one of the main challenges, says Pike.

“It’s a real mindset change to all those involved to work in that way,” says Pike. “But it’s a move to being more collaborative, progressive and focused on outcomes rather than commercial benefit – less selfish.”

Within the JV, Arcadis, which has a 40% share, carries out the front-end asset management, data analytics, FMECA and the maintenance strategies with Dura Vermeer carrying out the delivery work.  

Pike says success can be attributed to it having a very collaborative and high-performing team: “Yes, there are people from the different companies, but on the ground you wouldn’t know who is working for who.”

The measures have been so successful the joint venture now wants to try and roll them out elsewhere. In the UK, it is in talks with Network Rail, but it is also eyeing up some of the other high-profile operators such as High Speed 2, Transport for London and the Docklands Light Railway .

 

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