CASE STUDY

Industrial Manufacturer: AWS IoT + Data Lake for Plant Telemetry

An industrial manufacturer built AWS IoT pipelines + data lake covering 240 plants. Predictive-maintenance models on the data lake reduced unplanned downtime 47%.

May 9, 2026 · 2 min read · By admin

At a glance

Industry: Manufacturing
Topics: AWS · Cloud Services · Data Warehousing
Published: May 2026
Headline outcome: 47% Unplanned downtime: down 47%

Measured outcomes

What this programme actually delivered.

47%

Unplanned downtime: down 47%

78%

Predictive-maintenance flag accuracy: 78%

$28M

$28M annual savings on emergency repairs + lost production

The challenge

An industrial manufacturer collected 80M sensor readings daily across 240 plants but had no unified analytics platform. Each plant operated in isolation.

What we built

AWS IoT pipelines (Greengrass at the edge, Kinesis for streaming, S3 + Athena for analytics). Data lake with sensor + maintenance-history + production-quality data. Predictive-maintenance models using SageMaker.

Outcomes

Unplanned downtime: down 47%
Predictive-maintenance flag accuracy: 78%
Cross-plant best-practice identification automated
$28M annual savings on emergency repairs + lost production

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Industrial Manufacturer: AWS IoT + Data Lake for Plant Telemetry

What this programme actually delivered.

The challenge

What we built

Outcomes

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