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Komatsu revolutionizes manufacturing with Microsoft Azure and AI

Use case typePredictive maintenanceUpdated Jun 13, 2026

Komatsu, a leading Japanese manufacturer of heavy equipment, has harnessed the power of Microsoft Azure to optimize its manufacturing process. Initially rolling out its IoT system, KOM-MICS, in 2014, the company aimed at collecting data from machine tools and welding robots to perform predictive maintenance. The migration to Microsoft Azure in 2017 enabled Komatsu to scale its operations internationally, ensure better disaster recovery systems, and operate seamlessly in earthquake-prone regions. Recently, Komatsu has integrated AI solutions powered by Intelligent Edge, helping automate maintenance prediction and improving operational efficiency.

Organization
Komatsu
Industry
Manufacturing
Location
Japan
Published
July 2019

Reported outcomes

Strategic outcomes

Scale & capacityImproved international scalability of manufacturing operationsRisk & complianceEnsured business continuity with disaster recoveryNew product / capabilityEnabled predictive maintenance and automated insightsSpeed & agilityEnabled real-time equipment monitoring

Primary read

Use case focus

Showing 3 of 5

  • 1Predictive Maintenance for Manufacturing Equipment
  • 2Real-Time Production Line Monitoring and Optimization
  • 3Automated Downtime Analysis and Reporting
  • Difficulty maintaining production amid unpredictable market demand
  • Shortage of skilled workers due to aging demographics
  • Manual data collection limited optimization and visibility
  • Factory downtime and machine failures led to lost productivity
  • Need for accurate, real-time insights to optimize efficiency
  • Deployed KOM-MICS IoT system to collect machine and robot data
  • Migrated systems to Microsoft Azure for scalability and disaster recovery
  • Integrated Azure AI for predictive maintenance and automated insights
  • Leveraged Intelligent Edge solutions to enable real-time equipment monitoring
Technologies
Azure AIAzure IoT
  • Reduced equipment downtime through predictive maintenance
  • Improved international scalability of manufacturing operations
  • Enhanced operational efficiency with real-time analytics
  • Increased productivity despite labor shortages
  • Ensured business continuity with robust disaster recovery capabilities
Sources & evidence1
Live sourceStill referenced

The case's original source is still reachable.

  • Cited source last checked Jun 12, 2026 — ok (0/1 broken).

Measures whether this deployment's public evidence persists — not whether the system is still in production.

Groundedness: Unavailable
Primary source

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