Technology company Siemens has partnered with Sachsenmilch Leppersdorf GmbH to implement an artificial intelligence-powered predictive maintenance system at one of Europe’s most advanced milk processing plants.
The pilot project, based on Siemens’ Senseye Predictive Maintenance solution, aims to support uninterrupted operations and reduce equipment downtime in Sachsenmilch’s facility in Leppersdorf, Germany.
The dairy processor handles approximately 4.7 million litres of milk each day – equivalent to 170 truckloads – and produces a wide range of products, including butter, yoghurt, cheese, baby food ingredients, and bioethanol, Siemens said in a news release.
Operating 24/7 with high levels of automation, the facility requires consistent availability of equipment and reliable maintenance processes.
Siemens’ Senseye solution uses AI algorithms to monitor data from interconnected machinery, identify early signs of mechanical issues, and recommend timely maintenance actions.
During the pilot, the system was used to analyse data such as temperature, vibration, and frequency to detect potential faults before they led to breakdowns. Siemens also provided project management support and assisted in integrating new sensors and the Siplus CMS 1200 vibration monitoring system.
According to Sachsenmilch, one of the key challenges was interpreting large volumes of plant data and applying the insights to specific failure scenarios.
The pilot resulted in the early detection of a faulty pump, which the company said prevented unplanned downtime and avoided costs estimated in the low six-figure range.
Roland Ziepel, Technical Manager and head of project management at Sachsenmilch, said Siemens brought a combination of technical knowledge and project experience to the initiative.
“What we like about this project is that Siemens has know-how on both the technological and the technical sides as well as in project management,” Ziepel said. He added that following the initial implementation, Sachsenmilch was able to continue and complete the pilot independently.
Siemens said the project illustrates how predictive maintenance can be integrated into existing industrial processes to improve efficiency and reliability.
“We’re pleased that with Senseye Predictive Maintenance, we were able to successfully support Sachsenmilch in integrating a preventive maintenance strategy in its existing processes,” said Margherita Adragna, CEO of Customer Services at Siemens Digital Industries.
She added that further development of Siemens’ Maintenance Copilot Senseye is expected to support evolving maintenance needs.
Following the pilot, Sachsenmilch plans to expand the project by linking Senseye Predictive Maintenance to its SAP Plant Maintenance system.
The goal is to automate the transfer of maintenance alerts and further streamline planning processes. The company also intends to make greater use of Senseye’s maintenance recommendations to assist its teams.
