What challenges did HCL Technologies face before AI implementation?

Manufacturing enterprises faced challenges monitoring multiple disparate IT and IoT systems across plants. Unplanned downtime and lack of real-time KPI visibility caused losses in productivity and increased costs.

What was the impact of the AI solution?

Achieved 30% reduction in unplanned downtime losses. Increased asset productivity by approximately 15%. Reduced maintenance costs by around 30% through improved predictive maintenance.

Source

Microsoft

HCL Technologies Real-time Manufacturing Insights with Microsoft Azure

Use case typePredictive maintenanceUpdated Jun 13, 2026

HCL Technologies implemented the Real-time Manufacturing Insights (RMI) solution on Microsoft Azure IoT Edge and Azure IoT Hub to provide manufacturing plants real-time operational visibility and predictive analytics. The solution integrated multiple disparate IT and IoT systems to monitor asset health, synchronize production cycles, and reduce unplanned downtime across plants. Advanced Azure analytics services enabled predictive and prescriptive maintenance, reducing downtime losses by 30%, increasing asset productivity by 15%, and cutting maintenance costs by 30%. HCL's partnership and expertise in Azure cloud, IoT, and analytics contributed extensively to the project success.

Organization: HCL Technologies
Industry: Manufacturing
Location: India

Reported outcomes

−30%

timeTime & speed

+15%productivity−30%cost

Strategic outcomes

New product / capabilityBuilt unified real-time manufacturing insights platformBetter decisions & insightEnabled predictive and prescriptive maintenanceCustomer experience & trustProvided real-time operational alertsCost efficiencyReduced maintenance costs

Catalog median for time & speed deployments: −60% across 727 reported metrics. Compare benchmarks →

Primary read

Use case focus

Showing 2 of 2

1Predictive Maintenance
2IoT Integration

Manufacturing enterprises faced challenges monitoring multiple disparate IT and IoT systems across plants.
Unplanned downtime and lack of real-time KPI visibility caused losses in productivity and increased costs.

Implemented a unified IoT-driven real-time manufacturing insights platform using Microsoft Azure IoT Edge and Azure IoT Hub.
Leveraged Azure analytics to develop predictive and prescriptive maintenance models.
Provided plant management with real-time alerts and actionable insights to quickly address operational issues.

Technologies

Azure IoT Edge Azure IoT Hub Azure Analytics

Achieved 30% reduction in unplanned downtime losses.
Increased asset productivity by approximately 15%.
Reduced maintenance costs by around 30% through improved predictive maintenance.

Architecture

Azure IoT Edge and Azure IoT Hub platform integrating data from multiple manufacturing plants with advanced predictive analytics using Azure analytics services.

Implementation partners1

Dell Technologies

Sources & evidence1

Groundedness: 5/5

Primary source

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Customer evidence