Multiple global manufacturers prevent equipment downtime with predictive maintenance platform

A large, unnamed global manufacturer faced frequent unplanned equipment downtime due to fragmented and siloed data systems that obscured real-time insights. The company's vast IoT sensor network and extensive maintenance records were not effectively integrated, resulting in reactive rather than proactive maintenance approaches. By collaborating with Mutually Human and deploying Microsoft Fabric, the manufacturer centralized its data in a lakehouse architecture (OneLake), unified sources across ERP, sensors, and logs, and automated pipeline refreshes with Data Factory. Azure Machine Learning models, trained on years of failure events, delivered daily risk scores and live predictions for over 200 critical assets. Maintenance teams could act quickly using insights visualized on Power BI dashboards. Over a 90-day pilot, the centralized system enabled timely, actionable alerts, significantly reducing costly downtime. The platform now operates across multiple plants, transforming asset management, boosting efficiency, and supporting broader digital factory initiatives.