The arrival of the International Heavy Haul Association (IHHA) in Cape Town in September gave the leadership team at Ansys Rail an opportunity to reflect on the future of the rail industry both locally and in the rest of the world. With the process of digital transformation now well underway, it’s a time to look at what global peers are doing and to both learn from examples of excellence and, indeed, share some of our own.
Ansys Rail is already well established as a provider of innovative new solutions for trackside and onboard systems, as well as augmented operations systems that can assist drivers and workers to improve rail safety.
These improvements reflect a wider trend for the deployment of low power, low cost sensors which can provide real-time intelligence about the movements of rolling stock. In critical areas such as hot bearing detection, hot wheel detection and acoustic monitoring of track, Ansys Rail is embracing the opportunities provided by digitisation to adopt predictive maintenance regimes for safety and productivity.
Yet more exciting developments are ahead, says Business Development Lead of Ansys Rail Lebo Masekela, who picks out three areas which will see considerable investment in the year ahead.
The improvements in trackside monitoring have been exponential to date, but can get even better, says Masekela. One area of high potential is the use of autonomous drones to perform physical inspections of track, wagons and infrastructure such as bridges, allowing more regular inspections at lower cost.
Rail is also likely to emerge as a key driver for the adoption of 5G mobile technologies in countries such as South Africa, as more sensors mean increased demand for network capacity and high-speed data.
“While we wait for 5G capabilities to become common,” says Masekela, “we’ll continue to push the boundaries of what’s possible with 4G/LTE and mesh networking.”
And finally, with more data comes a greater need for analytics platforms that can interpret the information and improve resource allocation.
“Utilising network-centric decision algorithms to automate train scheduling and control will gain traction as information from track side and rolling stock information systems become more available,” says Masekela.