Unifying Railcar Monitoring Sensor Data, Maintenance Records, and Railcar Usage Information Through Big Data Processing for Optimizing Railcar Maintenance and Safety

Details

• Creators:
  Sharif, Hamid ; Hempel, Michael
• Corporate Creators:
  University of Nebraska--Lincoln. Dept. of Electrical and Computer Engineering ; University of Nebraska--Lincoln. Nebraska Transportation Center
• Corporate Contributors:
  University of Nebraska-Lincoln. University Transportation Center for Railway Safety ; United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Federal Highway Administration ; University of Texas Rio Grande Valley. University Transportation Center for Railway Safety
• Subject/TRT Terms:
  • Derailments
  • Information processing
  • Maintenance management
  • Optimization
  • Railroad safety
  • Railroad transportation
  • Sensors
  • Vehicle maintenance
  • Railroads
  • Maintenance
  More +
• Publication/ Report Number:
  26-1121-0018-010
• Resource Type:
  Tech Report
• Geographical Coverage:
  United States
• Edition:
  Final Report (October 2016 – June 2018)
• Corporate Publisher:
  University of Nebraska-Lincoln. University Transportation Center for Railway Safety
• Abstract:
  With this project, we investigated the use of Big Data Analytics to make rail transportation safer, by preventing derailments due to equipment failure. Railroads typically schedule railcar maintenance on best-practice intervals, which may not include the plethora of information available from their maintenance logs, track data, sensors information, bills of lading, manufacturer history, etc. This project explored the use of this data to adapt maintenance scheduling to reduce cost and increase safety. We showed the great potential inherent in this approach.
• Format:
  PDF
• Funding:
  DTRT13-G-UTC59
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/66371/dot_66371_DS1.pdf
• File Type:
  [PDF - 1.46 MB]
• Collection(s):
  University Transportation Centers
• Main Document Checksum:
  urn:sha256:6f0132811b068f130c6df68ead5e8bf9874423a7bf129f03fefc7dd2bcbb5119