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

Sharif, Hamid; Hempel, Michael; University of Nebraska--Lincoln. Dept. of Electrical and Computer Engineering; University of Nebraska--Lincoln. Nebraska Transportation Center

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

2018-08-01
By Sharif, Hamid ; Hempel, Michael

[PDF-1.46 MB]

English

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Details:

Creators:

Sharif, Hamid ; Hempel, Michael

Sharif, Hamid ; Hempel, Michael Less -
Corporate Creators:

University of Nebraska--Lincoln. Dept. of Electrical and Computer Engineering ; University of Nebraska--Lincoln. Nebraska Transportation Center

University of Nebraska--Lincoln. Dept. of Electrical and Computer Engineering ; University of Nebraska--Lincoln. Nebraska Transportation Center Less -
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

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 Less -
Subject/TRT Terms:

[+]

Data Analysis Derailments Information Processing Maintenance Maintenance Management Optimization Railroads Railroad Safety Railroad Transportation Scheduling Sensors Vehicle Maintenance
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
Collection(s):

University Transportation Centers
Main Document Checksum:

[+]

urn:sha256:6f0132811b068f130c6df68ead5e8bf9874423a7bf129f03fefc7dd2bcbb5119
Download URL:

https://rosap.ntl.bts.gov/view/dot/66371/dot_66371_DS1.pdf
File Type:

No Additional Files

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

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