Manufacturers in Poland minimize equipment downtime with predictive maintenance
A Polish manufacturing use case in which add. AI delivers a predictive maintenance solution leveraging Microsoft Azure. This solution combines machine learning with Azure IoT Hub, Stream Analytics, Data Lake, Synapse, and Databricks to reduce planned and unplanned downtime, understand machine failure reasons, and generate real-time predictive alerts. The offering integrates sensor and structured production data for forecasting failures and predictive scrap at both machine and product levels. Real-time analytics through Power BI allows empowered, data-driven decisions for plant staff. Implementation includes envisioning workshops, custom model development, data integration, and AI deployment. The product is distributed through a SaaS subscription model.
- Organization
- Polish Manufacturing Companies
- Industry
- Manufacturing
- Location
- Poland
- Published
- May 2025
Reported outcomes
Strategic outcomes
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Polish Manufacturing Companies
- Provider
- Microsoft
- Maturity
- Production
- Linked source
- azuremarketplace.microsoft.com
Operational dashboards and alerts via Power BI
Primary read
Use case focus
Showing 3 of 3
- 1Predictive Maintenance
- 2Real-time Asset Monitoring
- 3Equipment Failure Forecasting
- Frequent planned and unplanned machine downtime impacts productivity.
- Limited insights into the root causes of machinery failures.
- Maintenance based on conservative schedules leads to resource wastage.
- Reactive approaches increase production costs and risk.
- Lack of real-time asset health visibility for smart decision-making.
- Integration of machine and sensor data with Azure IoT Hub.
- Real-time stream processing and analytics with Azure Stream Analytics.
- Long-term data storage using Azure Data Lake, reporting with Azure Synapse.
- Predictive model creation and forecasting using Azure Databricks.
- Operational dashboards and alerts via Power BI.
- Security, orchestration, and monitoring with Azure supporting services (AD, Key Vault, Logic Apps, Functions, DevOps, Monitor).
- Reduced planned and unplanned downtime for manufacturing equipment.
- Improved productivity and asset utilization.
- Root causes for downtime and failures identified quickly.
- Maintenance actions optimized, cutting down resource waste.
- Empowered employees through real-time insights and predictive alerts.
Architecture
Machine and sensor data are ingested via Azure IoT Hub and processed in real-time with Stream Analytics. Power BI provides analytics and alerting, while raw and processed data is stored in Azure Data Lake for long-term access. Azure Synapse enables further dimensional data modeling and enriched analytics, and Azure Databricks is used for predictive modeling and forecasting on various timescales. Supporting Azure services manage security, orchestration, and system monitoring.
Sources & evidence1
- Customer explicitly identified
- Deployment status explicitly supported
- Technical implementation details available
- Recent evidence check available
- Last evidence check: Jul 22, 2026.
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.
AI-generated summary. Verify important details with the linked sources before relying on this case.
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