AI to improve predictive maintenance (RailwayTechnology)

No comments

The Palo Alto Research Centre (PARC) uses the industrial internet of things and artificial intelligence to develop new predictive rail maintenance and performance management technologies.

Passenger rail services in Japan have become a byword for efficiency, and the network spanning more than 27,000km remains one of the most utilised, punctual and least subsidised in the world.

Ensuring that operations and maintenance (O&M) work is carried out in a timely fashion is central to this success. In recent years, however, operators such as East Japan Railway Company, or JR East, have faced multiple challenges including aging infrastructure, a dearth of new train maintenance specialists due to Japan’s decreasing population, and spiralling costs alongside shrinking budgets.

To help improve train efficiency and safety for the six billion passengers that use JR East services every year, the company turned to PARC, an open innovation company based in Silicon Valley focused on predictive analytics using the industrial internet of things (IIoT).

Many of Japan’s capital-intense rail assets were deployed decades ago and JR East would obviously like to extract the maximum life out of them without compromising on safety. The shrinking population means that rail revenues are declining and so there is also pressure on O&M teams to be lean, plus a lot of more experienced technicians are beginning to retire.

Read full article

Written by Long Branch Mike