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Central Alberta train derailment prompts calls for enhanced analytics of railcar wheels
The agency says 1 million older wheels remain in service and better use of detector data could help prevent future derailments.
- On Thursday, the Transportation Safety Board recommended the rail industry use enhanced analytics on sensor data to identify failing wheels, following an investigation into a 2023 derailment near Uncas, Alberta.
- An April 5, 2023, derailment involving 18 Canadian National Railway Company grain cars left the tracks near Uncas, Alberta, after investigators determined a shattered rim on a wheel manufactured in 1991 caused the incident.
- Despite multiple visual inspections, no issues were identified before the failure; TSB Chair Yoan Marier noted that sensors failed to identify the increasing impact trend preceding "catastrophic rim failure."
- Approximately one million wheels manufactured before 2003 remain in service across Canada and the United States, and Marier stated that while most are likely safe, they possess a greater risk of failure.
- Transport Canada stated it will provide a formal response to the TSB within the timeline mandated by the Canadian Transportation Accident Investigation and Safety Board Act, emphasizing its commitment to strengthening rail safety.
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13 Articles
13 Articles
The Toronto Star+10 Reposted by 10 other sources
Transportation Safety Board calls for better wheel checks after train derailment
EDMONTON - The Transportation Safety Board says more needs to be done to ensure train car wheels are up to snuff after a broken rim led to a derailment east
·Toronto, Canada
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TSB calls for new process to identify deteriorating railcar wheels after 2023 derailment in Alberta
The Transportation Safety Board of Canada has revealed data trends that it says suggest railcar wheel failures could be predicted sooner by better leveraging data already available.
·Ottawa, Canada
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Coverage Details
Total News Sources13
Leaning Left8Leaning Right0Center3Last UpdatedBias Distribution73% Left
Bias Distribution
- 73% of the sources lean Left
73% Left
L 73%
C 27%
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