Viessmann builds an energy-efficient world with predictive maintenance on Databricks
ViessmannDelta Lake · Power BIViessmann, a family-owned provider of sustainable climate and renewable energy solutions, used the Databricks Data + AI Platform to process over 2.5TB of daily IoT machine data from its connected heating, ventilation, and solar devices, training ML models to detect anomalies like water pressure drops and forecast energy consumption and component lifetime for its remote service offering.
Overview
Viessmann, a family-owned provider of sustainable climate and renewable energy solutions, used the Databricks Data + AI Platform to process over 2.5TB of daily IoT machine data from its connected heating, ventilation, and solar devices, training ML models to detect anomalies like water pressure drops and forecast energy consumption and component lifetime for its remote service offering.
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Inspect the highlighted sourceThe challenge
Viessmann's previous data infrastructure created data silos, was costly to scale and had stability issues that impacted its ability to deliver ML-driven insights to those who needed them most — its customers.
The solution
With the Databricks Data + AI Platform, Viessmann is able to leverage IoT-enabled devices and monitoring apps to perform predictive maintenance and remote service sessions to help homes operate more efficiently and to reduce the number of onsite visits.
Reported business value
Through data-driven innovations like remote service powered by Databricks, Viessmann has reduced the number of mandatory onsite visits by up to 50%, which increased overall productivity for its partners and technical teams.
Sources
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