In an era where efficiency and sustainability are critical, Acond, a prominent European heat pump manufacturer, has adopted data-driven strategies to elevate its services. Faced with challenges in managing and analyzing data from its extensive network of installed heat pumps, the company adopted a cutting-edge Lakehouse platform. This transformation streamlined operations and significantly improved the reliability and efficiency of its heat pumps, demonstrating Acond's commitment to pioneering future energy solutions.

The Challenge: Data Analysis Delays and Limited Insights 

Acond, a leading manufacturer of heat pumps, faced challenges in its journey towards digital transformation. The core limitation revolved around the slow data analysis processes from installed pumps, which were missing a comprehensive view and timely insights. Each pump, equipped with an SD card, gathered operational data crucial for understanding performance and diagnosing issues. However, whenever a pump encountered a problem, the data gathering and aggregation process by a technician took about 15 minutes per pump—a considerable time investment given the growing number of pumps serviced. This not only caused delays but also lacked the possibility to manage pumps remotely.

The Solution: Unified Data Platform Transforms Heat Pump Management 

To overcome the challenges, Acond embarked on creating a unified data platform leveraging the Databricks Lakehouse. They cooperated with the partner DataSentics, a Data AI center of excellence within Eviden. The new platform was meant to use data from several thousand modern heat pumps, collating dozens of IoT sensors and hundreds of detailed parameters for each pump, including both historical data and real-time updates.

Real-time adjustments are key in the new system, quickly resolving pump issues and boosting efficiency. Technicians can now manage and modify settings for all or specific groups of pumps, revolutionizing maintenance.
Machine learning integration is crucial, enabling anomaly detection in pump behavior for remote predictive maintenance. This uses historical data to identify typical device states, improving Acond's efficiency and customer satisfaction through reliable pump performance.
The scalable Databricks Lakehouse platform, on Microsoft Azure, adapts to Acond's growth and increasing device numbers, continuing to offer real-time insights and management capabilities.

"The new Aconds’ IoT data platform integrates over 1 billion historical data entries, connects with more than 5000 devices, and processes up to 60 distinct measurements at 5s cycles, generating over 30 million new rows daily. By leveraging Databricks Lakehouse, we have streamlined real-time analytics and predictive maintenance, improving efficiency and scalability while minimizing data aggregation efforts for technicians."

Jan Kelbl, Technical Expert, DataSentics

The Benefits: Enhanced Efficiency and Customer Personalization 

The unified data platform has greatly benefited Acond and its customers. It allows real-time management of multiple pumps, reducing delays and improving efficiency. Technicians can swiftly adjust pumps, offering personalized service based on real-time data.

The platform's integration of machine learning for anomaly detection helps identify devices with high energy use and increased wear, aiding predictive maintenance. This proactive approach minimizes onsite visits, saving time and resources.

A key customer benefit is the AI-driven personalization of each pump, previously done on request, now automatic. This ensures optimal performance and customer satisfaction.

Furthermore, the scalable platform supports Acond's growth and provides valuable insights for R&D, fostering innovation and continuous improvement.