Deep Dive
Using data science to better understand and maintain rolling stock performance.
Author: Dr. Allan M. Zarembski
Big Data Journey: From Collection to Analysis to Predictive Use
RAILWAY AGE, MARCH 2020 ISSUE: The December 2019 Big Data in Railroad Maintenance Planning Conference, held at the University of Delaware, continued to highlight the advances the railroad industry is making in addressing the growing volume of data from inspection and other systems, and learning how to apply it. This was clearly shown in the keynote address, where the keynote speaker, Jeffrey D. Knueppel, P.E., now retired as General Manager of Southeastern Pennsylvania Transportation Authority (SEPTA) presented how his agency is already using a range of data collection, data analysis and data management tools in the everyday running of SEPTA. In fact, he titled his presentation “SEPTA’s Journey Into Big Data” and presented a range of Big Data applications that are currently implemented or being implemented on SEPTA.
Big Data drives big results
Railway Age, February 2019: As railroads continue to expand their data collection technologies across all of their operational areas, they simultaneously continue to expand their ability to analyze this data and convert the data into actionable information—in other words, to generate information that can be directly used in their operation or maintenance activities.
Rolling with Big Data
The emerging role of Data Science, commonly known as “Big Data” in railroad maintenance, was discussed earlier in Railway Age (“Better Railroading Through Big Data.”) As noted, railroads are developing and implementing new generations of sophisticated inspection and monitoring systems, and as a result are finding themselves collecting large volumes of data.
Better railroading through Big Data
As railroads develop and implement new generations of sophisticated inspection and monitoring systems, they find themselves collecting large volumes of data, at increased frequencies across a variety of interrelated systems.