INDIA: Siemens Mobility has officially handed over the first of 1 200 WAG D9 electric freight locomotives which it is supplying to Indian Railways. The company also opened a maintenance depot in Visakhapatnam.
‘With our leading technology, we are supporting the country’s goal of shifting more freight to rail, boosting logistics efficiency, and significantly reducing CO₂ emissions for decades to come’, said Siemens Mobility CEO Michael Peter on May 4.
‘Together, we are bringing one of the world’s most powerful and energy-efficient freight locomotives into service – manufactured and maintained in India.’
Largest single locomotive order in Siemens history
In January 2023 Siemens Mobility beat Alstom to win a Rs260bn lifecycle partnership contract to design, manufacture and commission 1 200 locomotives over 11 years and provide 35 years of full-service maintenance. It is the largest single locomotive order in the history of Siemens Mobility and the largest order in the history of Siemens India, which was established in 1867.
The WAG D9 (EF-9K) locomotives are being assembled at the Indian Railways factory in Dahod, with 89% domestic content and work undertaken by IR staff. The IGBT traction equipment is produced at Siemens Mobility factories in India. Wabtec is supplying ILS series braking systems from its Hosur plant and provides maintenance services in an Rs13bn contract.
The 1 676 mm gauge 22.5 tonne axleload WAG D9 locos are India’s most powerful six-axle electric freight locos at 9 000 hp, with the ability to haul loads of up to 5 800 tonnes on specified gradients or 4 500 tonne double-stack container trains at 120 km/h on the country’s Dedicated Freight Corridors.
Siemens said the locos are Indian Railways’ first to be successfully tested to the European standard EN 14363 for dynamic behaviour.
Maintenance will be provided through a network of four depots at Visakhapatnam, Raipur, Kharagpur and Pune, with Siemens Mobility using its Railigent X digital platform to support condition monitoring, predictive maintenance and data-driven performance optimisation.