MTA Long Island Rail Road automates asset management to improve public safety

Published on 16-Jul-2010

Validated on 15 Aug 2013

"Our goal is to design and develop an intelligent asset management and maintenance system, which is critical to the success of the Rail Road and the services we provide to our customers." - Vincent Mezzanotte, Chief Information Officer, MTA Long Island Rail Road

Customer:
Long Island Rail Road

Industry:
Travel & Transportation

Deployment country:
United States

Solution:
C-Suite Framework, Dynamic Infrastructure, Cloud & Service Management, Service Management, Smart Work, Smarter Planet

Smarter Planet:
Smarter Infrastructure, Smarter Rail

Overview

The Long Island Rail Road (LIRR) is the largest commuter rail system in North America. It operates 1,180 rail cars that move more than 300,000 passengers daily across 700 miles of track. It’s owned by the Metropolitan Transportation Authority (MTA).

Business need:
Operating the largest commuter rail system in North America, Long Island Rail Road carries more than 300,000 passengers each day on over 700 miles of track. And, with its equipment exposed to the elements and experiencing everyday wear and tear, the organization must closely monitor the status of its rail assets to maintain reliable operations and encourage public safety. The rail operator wanted an integrated solution to strengthen and better coordinate its repair efforts.

Solution:
Long Island Rail Road will implement a new transportation and asset management solution to provide a single software interface in support of all maintenance activity for its rolling stock and related assets. The solution will integrate existing rail operations systems and automate repair efforts by tracking the life expectancy of deployed equipment and dispatching repair orders before units break down.

Benefits:
· Helps maximize the life cycle of components with real-time visibility into equipment states
· Delivers increased visibility into maintenance processes, simplifying governance efforts and encouraging improved maintenance coordination
· Creates a safer and more reliable environment for passengers by increasing the predictability of asset performance

Case Study

The Long Island Rail Road (LIRR) is the largest commuter rail system in North America. It operates 1,180 rail cars that move more than 300,000 passengers daily across 700 miles of track. It’s owned by the Metropolitan Transportation Authority (MTA).

The Need

Operating the largest commuter rail system in North America, Long Island Rail Road carries more than 300,000 passengers each day on over 700 miles of track. And, with its equipment exposed to the elements and experiencing everyday wear and tear, the organization must closely monitor the status of its rail assets to maintain reliable operations and encourage public safety. The rail operator wanted an integrated solution to strengthen and better coordinate its repair efforts.

The Solution

Long Island Rail Road will implement a new transportation and asset management solution to provide a single software interface in support of all maintenance activity for its rolling stock and related assets. The solution will integrate existing rail operations systems and automate repair efforts by tracking the life expectancy of deployed equipment and dispatching repair orders before units break down.

What Makes it Smarter

  • Helps maximize the life cycle of components with real-time visibility into equipment states
  • Delivers increased visibility into maintenance processes, simplifying governance efforts and encouraging improved maintenance coordination
  • Creates a safer and more reliable environment for passengers by increasing the predictability of asset performance

For more information

Contact your IBM sales representative or IBM Business Partner. Visit us at: ibm.com/travel

Products and services used

IBM products and services that were used in this case study.

Software:
Maximo Mobile Work Manager, Maximo for Transportation

Service:
GBS SCM: Enterprise Asset Management

Legal Information

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Produced in the United States
June 2010
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