AI case study

Kawasaki Heavy IndustriesRailroad track maintenance

Visual checks halted freight. Now, edge AI spots faults and optimizes routing, saving 26,000 hours annually.

Published|1 year ago

Key results

Annual Industry Savings
$218.4M
Annual MTM Savings
26k hours
Weekly Time Savings
5 hours
vs manual scheduling

Result highlights

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The story

Context

A heavy machinery manufacturer serving the North American Class I railroad network, which consists of over 140,000 miles of track across diverse terrain.

Challenge

Inspectors must visually examine rails and fasteners to spot faults, a manual process that requires halting profitable freight operations. This...

Solution
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Quotes

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The company

Kawasaki Heavy Industries logo

Kawasaki Heavy Industries

global.kawasaki.com

Heavy industry manufacturer for aerospace, energy, mobility, and industrial sectors.

IndustryTransportation & Logistics
LocationTokyo, Japan
Employees10K-50K
Founded1896

The AI provider

NVIDIA is a technology company that specializes in semiconductors, graphics processing units, and artificial intelligence for applications in data centers, gaming, and more.

IndustryTechnology
LocationSanta Clara, California, United States
Employees10K-50K
Founded1993

The implementation partner

Slalom Build logo

Slalom Build

slalombuild.com

Partnered with Kawasaki to build its AI-driven track maintenance and inspection platform.

IndustryTechnology
LocationSeattle, WA, USA
Employees10K-50K
Founded2001

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