Irish Rail will be deploying Nexala’s R2M for fault diagnostics and work scheduling across its CAF Class 29000 commuter fleet.
The R2M system, a combination of shore-based software and on-train equipment, provides real-time alerts on any faults in the fleet, to the maintenance depots.
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Irish Rail will be also able to avoid future failures by undertaking pre-emptive maintenance with the help of the R2M system.
Automation of manual tasks will enable railway operators to streamline maintenance costs, as well as provide efficiencies, Nexala said.
Dublin-based Nexala has been providing on-premise and software as a service (SaaS) solutions for the rail, bus, tram and transport infrastructure sectors for the past two decades.
The company was acquired by US-based Trimble in December 2014.
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By GlobalDataThe latest contract from Irish Rail follows the successful implementation of the R2M system across the operator’s Hyundai Rotem class 22000 DMU fleet.
Irish Rail chief mechanical engineer Peter Smyth said: "Nexala’s real-time remote diagnostic system was successfully rolled out across our InterCity Class 22000 fleet in 2013.
"This has resulted in significant maintenance savings, incident prevention and recovery, and improved operational efficiencies.
"We look forward to equipping the CAF 29000 commuter fleet so we can experience similar benefits to the implementation on the InterCity Class 22000 fleet."
The CAF 29000 commuter fleet will be equipped with the on-board Nexala Control Unit (NCU), communications and R2M software.
The equipment collects data from various sources including door control units, alarm concentrators, fuel systems, TELOC data recorders, and train management and diagnostic system (TMDS) on-board computers and transmits them to the data centre where the maintenance teams can monitor the fleet in real-time.
The Nexala system also offers reporting and trend analysis, thereby assisting the operator in better fleet maintenance.
Image: The software and related equipment will be deployed on Irish Rail’s CAF class 29000 trains. Photo: courtesy of Terence Wiki via Wikipedia.
