AI case study

Delhi Metro Rail Corporation (DMRC)Predictive maintenance

Teams manually monitored 395km of track. Now, AI predicts faults like wire sagging in real time, targeting 20% less downtime.

Published|3 months ago

Key results

Planning Time Savings
~15%
Downtime Reduction
10-20%

Result highlights

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The story

Context

One of Asia's largest transit networks carries more than seven million daily commuters across 395 kilometers of track and 289 stations in the Delhi-NCR region.

Challenge

Critical data was trapped in fragmented systems, forcing teams to rely on manual monitoring and reactive maintenance for assets ranging from rolling...

Solution
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Quotes

The company

Delhi Metro Rail Corporation (DMRC) logo

Delhi Metro Rail Corporation (DMRC)

delhimetrorail.com

Public rail transit network for Delhi and its surrounding satellite cities.

IndustryGovernment & Public Sector
LocationNew Delhi, DL, India
Employees10K-50K
Founded1995

The implementation partner

Deloitte logo

Deloitte

deloitte.com
Role in this case study

Helped DMRC build a Data Center of Excellence (DCoE) on Google Cloud.

IndustryProfessional Services
LocationNew York, NY, USA
Employees100K+
Founded1845

The vendor

Cloud computing services, AI infrastructure, and data analytics platforms for enterprises.

IndustryTechnology
LocationMountain View, CA, USA
Employees100K+
Founded1998

Use case

Delhi Metro Rail Corporation (DMRC)'s Predictive maintenance is part of this use case:

Predictive Maintenance
20 case studies(+50% YoY)
Proven impact?
LowModerateVery Strong
8.3Very strong
13.5Very strongwithin Operations

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