Rail hot box detector analytics for improved safety
Our customer is a Class 1 railroad in North America, operating in 10 central U.S states, as well as the north-eastern states of Mexico and into Canada. It has over 13,000 freight cars and 1,044 locomotives, and their rail network comprises approximately 6,600 route miles that link commercial and industrial markets in the United States and Mexico.
The goal for our customer was to be able to get a maintenance crew out to fix a hot box detector before it could malfunction and stop any trains, which costing the customer a lot of money. But with multiple tracks throughout the country and massive amounts of data being generated, crews weren’t able to interpret the data and get to the problematic HBDs in time.
As a part of the solution, CloudMoyo enabled consumption of streaming data from wayside equipment by ingesting large volumes of data from the hot box detector into an Azure Data Lake. A data warehouse was created with proper data validation and data governance process was set up. Future proofing solution in terms of scalability, reliability by using the Azure Data Platform. Thus, future proofing solution in terms of scalability, reliability by using the Azure Data Platform.
The hot box detector analytics solution helped them overcome challenges like:
- High frequency of inspection
- Manual inspection
- Equipment failure
- Poor detection of a derailment
- Unnecessary delays caused by a false alarm
Download the case study to find out how CloudMoyo developed an operational data store (ODS) using Microsoft SQL Server to handle 16,000+ contracts encompassing NDA, SOW, MSA, CORF, and ADD agreements, which were extracted and loaded in record time and delivered multiple benefits to the customer.
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