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Canadian Pacific 

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Calgary, AB T2C 4X9 

Canada

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CP is constantly striving to be the industry’s most innovative Class I railway

Innovation + Data Analytics

We’re at the forefront of predictive analytics in our industry for locomotives, railcars and track infrastructure to ensure your shipments move more consistently, reliably and safely. Innovations like Cold Wheel Technology are helping us predict and prevent safety incidents and service interruptions before they occur.

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CP’s patented algorithm has resulted in a 95% reduction in online wheel bearing related failures after algorithm deployment in 2016, keeping our trains moving quickly and safely across our network.

Train Inspection Portal System

By utilizing 35 cameras, we are able to inspect all passing railcars and locomotives, capturing up to 72 high resolution images per car. They enable us to identify missing bolts, bent or broken brake rigging, open bottom gates, broken couple systems and draft arrangements.

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2018

Our predictive analytics innovation was recognized with a safety award by the Railway Association of Canada in 2018.

Cold Wheel Technology – Automated Brake Effectiveness (ABE)

By measuring wheel temperatures following a grade where brake application is required, we can identify which cars require further inspection for brake maintenance. This helps reduce terminal dwell time.

Wheel Life Forecasting

This technology predicts wheel life using both detector and car repair data, allowing us to narrow wheel wear limits down to a month.

Cracked Wheel Detection

This system prevents derailments by identifying wheel defects that would otherwise be missed with visual inspections. It detects wheels for removal that have the potential to break when hauling heavy loads.

Wheel Impact Load Detectors

Our wheel impact load detectors precisely measure and produce alerts for overweight or severely imbalanced railcars, allowing us to forecast individual freight car wheel life and be more proactive to avoid service interruptions.

Predictive Bearing Failure Using Acoustic Sensors

By using acoustic detectors we are able to predict when wheel bearings are going to fail three months in advance. By pulling and repairing assets as soon as issues are detected, we’ve reduced online wheel bearing related failures by 95% after algorithm deployment in 2016.

Train Air Flow Monitoring

This system monitors locomotive event recorder data in real-time to identify airflow issues, reducing service interruptions by 50% in winter 2019.

Broken Rail Detection in Dark Territory

This technology aims to prevent derailments by identifying broken rails and halting train movement on that section of the track in non-signalled (dark) territory.

Autonomous Track Geometry Measurement System

This system improves service by reducing derailments and unplanned work outages using a non-contact, laser-based optical measuring system, providing near real-time defect detection to predict track deterioration.

Enhanced Rail Flaw Detection

Enhanced Rail Flaw Detection enables rolling contact fatigue to be proactively identified and managed through grinding or rail replacement.

Track Inspection

This technology identifies possible track defects by measuring vertical and horizontal acceleration, and identifies unusual movements. Overall, it enables us to analyze more than 600,000 miles of data annually on our network.

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CP is at the forefront of the railroad industry when it comes to using predictive analytics to improve service and safety. While many of our competitors are making major investments in expensive machine learning tools that deliver limited results, at CP we’re solving real operating problems that deliver value for our customers.

Dr. Kyle Mulligan
Chief Engineer

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