Indian Railways to use artificial intelligence to manage track maintenance blocks


NEW DELHI: Artificial intelligence (AI) that can diagnose the condition of rail tracks will be used by the railways to prepare a repair and replacement calendar and improve punctuality of trains, according to an official. In India, unplanned track maintenance work is often cited as a reason why train operations descend into chaos. Use of AI, the official said, will ensure that at least 90% of trains run on time as routine maintenance work would be planned in advance on the basis of the AI-aided calendar. All large maintenance blocks will be taken up only on Sundays to minimise the impact of train delays, the official said, adding that the national transporter is already procuring automatic track detection machines which, through AI, can predict the life of tracks and track joints. The move is also seen substantially reducing the number of train accidents.

Kyoei Sangyo says subsidiary falsified life raft maintenance data

The Japan Times

Kyoei Sangyo Co. has revealed that a life raft maintenance subsidiary has skipped some safety inspection steps or manipulated maintenance records at its sales office in Hiroshima Prefecture. After receiving the report Friday from Kyoei Sangyo, a Tokyo-based technology firm, the transport ministry ordered Kyoei Marine Technology Co.'s office in Fukuyama to halt its maintenance operations over the violation. The ministry will launch on-site inspections at life raft maintenance companies across Japan by Nov. 9 to check for similar improper cases. According to Kyoei Sangyo and other sources, the irregularities at the Fukuyama office may have started in August 2002. Inspectors there are believed to have skipped tests to confirm air leaks for a total of 326 cargo ships and ferries as well as tests for emergency slides.

Southwest Airlines Plans Maintenance Facility at BWI

U.S. News

The Hogan administration says the project is expected to create 450 construction and maintenance jobs over the next three years and support hundreds of additional maintenance jobs over the next two decades. It's expected to cost $130 million, with $80 million coming from Southwest to build it and $50 million from the Maryland Aviation Administration for infrastructure.

Kawasaki Heavy looking to buy U.S. train maintenance firm

The Japan Times

Kawasaki Heavy Industries Ltd., the maker of New York City subway trains, is seeking to buy a train maintenance company in the U.S. to help increase its services lineup and boost profit margins. "The costs for maintenance are largely fixed," Yoshinori Kanehana, president of the company, said in an interview Tuesday. "By bringing that in-house, we can cut costs and increase profit." Kawasaki Heavy, which gets a quarter of its revenue from the U.S., its biggest market outside Japan, is considering spending "several billion yen" to acquire a U.S. company, he said. The Kobe-based company is competing with other Asian train makers such as Hitachi Ltd. and CRRC Corp. in North America, as well as Bombardier Inc. Kawasaki Heavy, which also supplies bullet trains to Japan and Taiwan, is targeting a 36 percent increase in rolling stock sales to 200 billion by the year starting April 2018, from 147 billion in the 12 months through March, it said in May.

Artificial Intelligence Will Help Indian Railways Predict The Life Of Tracks


The Economic Times has reported that Indian Railways will put artificial intelligence to use to manage track maintenance blocks. An official from the railways said that the artificial intelligence technology, which is capable of detecting the condition of railway tracks, would soon be deployed to prepare a repair and replacement calendar. Indian railways accounts its unplanned track maintenance work for its notoriety in the world for its delayed operations. With the use of artificial intelligence, it is expected that at least 90% of trains will run on time since the maintenance work would be planned in advance. The AI will help in creating a calendar according to which the maintenance work can be scheduled beforehand leading to trains running punctually.