Digital Twin in the Railroad Industry

By Wes Kaisershot, PE
VP, Engineering
Current ARDA Technology Committee Co-Chair

April 13, 1970: NASA astronauts Jim Lovell, Jack Swigert, and Fred Haise were in trouble as the term
“Houston, we’ve had a problem…” was famously coined. The proposed Apollo 13 lunar landing mission
was aborted early when an oxygen tank failed two days into the mission. The three astronauts were left
in peril some 210,000 miles from earth, unable to see the damage to their spacecraft. Houston Mission
Control experts used spacecraft simulators, computer programs, real-time data, and astronaut reported
information to produce what was, in essence, a “replica (twin)” of the real NASA spacecraft. This was the
first occurrence of a digital “twin” analysis being used to correct the forces of a damaged spacecraft. In
this case, it involved, and ultimately succeeded in, the safe return to earth for our three astronauts.

The railroad industry is no stranger to the technological revolution. In any industry, an organization’s
success can be determined by its willingness to embrace technological change and updated efficiencies.
Without technological adoption, a company or industry will be left behind by those that embrace the
change and modern efficiencies of the industry. “digital twin” is more than a buzzword in technology
circles as many are wondering just what a digital twin is.

Understanding Digital Twin

Four Applications in Railroads

There are four ways digital twin technology is being adopted by the railroad industry.

1. Predictive Maintenance: To prevent failures and optimize performance, critical rail assets such
   as engines, cars, tracks, and other equipment are monitored by digital models. These models can
   estimate the effects of aging, environmental, and normal wear and tear conditions on the
   equipment and illustrate when they may need repair or replacement. This assists in proactive
   maintenance and preventive solutions that could cause service delay for railroad companies.
   Union Pacific Railroad has used digital twin modeling to predict the condition of various
   locomotives in real-time and predict maintenance issues before they arise.
2. Simulations: Digital twin technology is assisting the railroad industry by simulating different
   scenarios of train movements to improve efficiencies and scheduling along considerable lengths
   of track. Norfolk Southern Railway recently used digital twin simulation to reduce fuel
   consumption and improve on-time performance for their nationwide system.
3. Real Estate: Digital twin can track and model right-of-way parcel locations and conditions of
   assets, such as railcars, locomotives, underground utilities, and other railroad equipment. The
   model can produce and illuminate key components and values to a railway’s real estate assets. It
   can serve as a predictive tool to determine what parcels are in appraisal, acquisition, or other
   status tracking property needs.
4. Predictive Analytics: Digital twin use along with modern sensing technology, can be used by
   railways to collect and analyze data with sensors, cameras, and other devices in predictive
   methods to mitigate risk with operations issues and safety.
   Calculative Benefits to digital twin use:

Benefits of Digital Twin in Railroads

• Reduced downtime and maintenance dollars
  • Digital twin predictive analysis runs the scenario through the “twin”
  •  Railway asset maintenance is streamlined and more efficient
• Better production during manufacturing
  • During manufacturing of railway assets, infrastructure, and track
  • Troubleshoot during the design and production of railroad iron assets
• Optimized supply chain
  • Better data on supply chains for railway routes
  • Collaborate with real-time customer supply data
  • Inventory levels and logistics in the digital twin
• Safety
  • Maintain the highest priority for both railway employees, customers, and the public along railroad routes
  • Simulate hazardous conditions and test safety measures without putting humans at risk

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• Summary: Technology advancement, such as digital twin, can assist the railway in predictive analysis,
  simulations, asset management, and more. This modeling and strategic approach is key to the railroad
  industry’s advancement. Class I and Short Line railway companies are no stranger to the use of cuttingedge technology, but the adoption of digital twin promises that bright, efficient, productive days lie
  ahead for railways in North America and beyond.