(Image: Supplied)
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Australian giant Downer has a 30-year contract with the New South Wales government to manage and maintain its fleet of 78 Waratah trains that operate in the greater Sydney metro area. With 2041 not approaching any time soon, the company recognised a perfect opportunity to maximise technology to make the most of its data and plan for proactive, rather than reactive, maintenance of Sydney’s trains.
In December 2016, the NSW government ordered 24 Waratah Series 2 trains under its Sydney Growth Trains Project and in February 2019, announced the decision to order 17 more trains. The new trains are touted as providing passengers with improved safety and comfort, fitted with air-con, more CCTV cameras, and improved accessibility.
Downer general manager of Digital Technology and Innovation Mike Ayling said his company saw this as the perfect opportunity to leverage additional sensor data from the fleet.
As each Waratah train pulls in and out of a Sydney station, more than 300 Internet of Things (IoT) sensors and almost 90 cameras silently capture data and record video. Every 10 minutes, 30,000 signals are sent from the train to Downer.
According to Ayling, those 30,000 signals represent the train’s digital DNA.
“Essentially, these are trains with brains. We’re getting 30,000 signals from each train every 10 minutes. You extrapolate that out, we now have billions of data points since the inception of the fleet,” Ayling said.
“We’re using those sensors to tell us about the health of the train — it’s almost like having a blood pressure reading.”
(Image: Supplied)
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Downer deployed a Microsoft Azure-based intelligent solution that ingests sensor data from Sydney’s fleet of Waratah trains and spits out something useful that is easily digestible to engineers and other staff.
The Azure IoT Hub feeds stream analytics into an Azure Data Lake Store and Azure SQL database. Access is managed by Azure Active Directory with Power BI providing analytics and reporting. Downer’s TrainDNA platform ingests the data and uses Azure machine learning to make sense of it.
The collaboration followed Downer turning to Microsoft in 2017 to form a partnership aimed at developing and marketing cloud-based solutions and services for specific industry sectors. The alliance, according to Microsoft, sees “both parties bring their technology and sector specific know-how to the table”, and was designed to help “accelerate the rate at which transformational value could be unlocked for business”.
Speaking with media at the Auburn Maintenance Centre in Sydney, Ayling said the platform was built with two audiences in mind: Firstly for the fleet of support officers who are working with Sydney Trains in their operations centre making sure the trains that are on the network are running all the time; and for the fleet engineers who are looking at the longer-term trends.
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