Alstom has integrated the latest technological innovations, from data-driven predictive maintenance to artificial intelligence and virtual reality, into many different aspects of the business.
Here, we look at how the global and Australian transport leader has used technology to improve safety, efficiency and reliability across the board.
A key strategic pillar
Rikki Toms, Alstom ANZ’s Operational Excellence Manager, said innovation is a key strategic pillar for the company.
“Alstom invests considerably in innovation across all aspects of the product life cycle, from the design of trains and trams through to the physical manufacturing and repair of components and asset maintenance activities.
“Being a global company across different mobility solutions, we leverage learnings across our depots all around the world to deliver the best possible solutions for our customers.”
Toms said Alstom’s focus on product or strategic innovation isn’t to the detriment of other areas like continuous improvement.
“Some businesses are strong in strategic innovation while others are great on incremental continuous improvement, yet I believe we are strong in both areas,” she said. “Alstom has a strong lean culture, driving out waste and embedding efficient processes.”
Reducing downtime
Alstom uses predictive maintenance to reduce train downtime and improve operational performance.
Its predictive maintenance tool, HealthHub, can monitor the condition of trains, infrastructure and signalling assets using advanced data analytics.
It works in tandem with TrainScanner, an automated diagnostics portal that measures the health of three key consumables of a train as it moves through the portal: wheels, brake pads and pantograph carbon strips.
“HealthHub is our eyes, our connection to the train,” said Glen Smith, Alstom’s Services Director for New South Wales and Western Australia.
“It collects data constantly, in real-time, so at any point we can see the health of a train, the speed, condition of sub-systems – right down to things like the temperature inside the train cars.”
Smith said the frequency of data being collected by HealthHub and TrainScanner helps reduce service failures and increase the availability of trains, saving operators time and money.
“Historically, when this data collection was done manually, it couldn’t be done as frequently or as accurately,” he said.
“Because of the volume of highly accurate, real-time data that we have now, we get warnings that there is a failure about to occur, and our engineers and maintenance teams can intervene straight away.
“There’s been a major shift from reactive to predictive maintenance and Alstom is at the forefront of that.”
HealthHub can also be used to adjust the train in real time.
Smith said: “Something like passenger comfort might sound like a trivial thing, but for passengers it’s really important. Our air conditioning and lighting on the trains is all algorithm-based, using the data we’re collecting.
“We might see that a certain train or even a particular train car is hotter than what we would like in terms of passenger comfort, so we can increase the air conditioning, or it can also happen automatically.
“Previously this would have been done by the driver, who might be experiencing a different temperature in the cabin. We’ve now separated those systems, with the driver able to control their own area.”
Smith said placing passenger experience at the core of design plays an essential role in encouraging more people to use rail transport.
“Our on-board systems support this in increasingly more sophisticated ways,” Smith said.
Saving money – and the environment
Smith said that Alstom’s use of predictive maintenance reduces costs for its customers while delivering a range of environment benefits.
Before predictive maintenance, refurbishments would have been done based on fixed time periods or distance travelled by the train.
“Maintenance was sometimes being carried out before it was needed,” he said.
Each component on a train can only be refurbished or made usable again a certain number of times, before replacement is required.
However, Alstom’s predictive maintenance technology extends the intervals of time, or the kilometres travelled, between those refurbishments.
“By collecting data on the health of each component, you can gauge how much time you have before that major intervention, safely and without risking failures in service,” Smith said.
“This reduces the likelihood that we will need to replace that component during the train’s life. By extension, this delivers a much better sustainability outcome, because you’re using fewer components, while also reducing life cycle costs.
“Our trams, for example, are up over 95 per cent in terms of the overall vehicle being able to be reused.”
Virtual reality
At some of its sites around the world, Alstom uses virtual reality (VR) to train its drivers.
“I’ve just come back from an Alstom services site in India, where we are using virtual reality to train drivers in the specifics of an Alstom locomotive,” Toms said.
“These drivers already know how to drive a train, but our train simulator is set up in exactly the same way as our actual locomotive, so drivers can physically familiarise themselves with the layout and components on the train.”
Alstom also uses VR for a number of maintenance-related activities.
“You can program in just about any maintenance activity and simulate it, which can add a considerable amount of value.
“You might just realise – ‘Oh, I can’t actually get a forklift into an area of the warehouse due to space constraints,’ or ‘I can’t access a specific bolt under the body of the train with a standard sized tool.’
“This enables us to redesign our approach to achieve optimal outcomes.”
Digital depot
Toms explained how Alstom’s Digital Depot provides an end-to-end strategy of everything from the HealthHub to real-time fleet management to digital documentation of safety maintenance and train performance.
“You can see a train from the time that it’s designed until its end-of-life, and it looks at every aspect and digitalises the key activities within that,” she said.
“Alstom globally, and our depots around the world, are working towards a Digital Depot of the future, which will include things like virtual reality, digital twins, and remote monitoring of train performance.”
Digital twins
Smith said the use of digital twins is an exciting growth area for Alstom.
“At the moment, we are using digital twins in a targeted way – so we might pick a particular asset that we have and target the maintenance outcome for that asset,” he said.
“We use it for subsystems, to see if we can improve their performance or do less maintenance on it across its life cycle.”
He said digital twins allow Alstom to compare what they see in the field with an engineering or theoretical outcome.
“You can see that variance quite quickly because you’ve got a hypothetical, digital model, versus an in-field observed life and performance.
“I think in the future digital twins will become an even more useful tool across a wide range of subsystems.”
Artificial intelligence
Toms said Alstom is making use of artificial intelligence (AI) to improve many aspects of the business, with a dedicated “Innovation Station” team in Singapore that investigates breakthrough technology and pushes the boundaries of what’s possible. The team in Singapore supports the wider Asia-Pacific region, ensuring that Alstom’s global innovations are available to all markets across the world.
“They look at innovative processes, innovative technology and innovative design,” she said.
“They’re looking at every element of productivity, including our own efficiencies and productivities in the back office.
“At the moment, we’re trialing AI co-pilot [a type of AI-powered virtual assistant] across the whole organisation.
“No stone is left unturned in the pursuit of continuous improvement.”
Smith added that AI is also being used to speed up maintenance processes.
“If you need to look up a procedure or maintenance instruction, historically you might have had to trawl through a library of documents to find which one applies.
“Alstom now has AI tools that allow us to interact with the system like it’s a person, so you can ask it a question and it will give you the document you need and tell you the procedure that applies. So, something that would have taken a couple of hours to research now takes five to ten minutes.
“Our engineering teams are becoming more and more efficient thanks to AI, and I think it’s just the tip of the iceberg.”
