A dairy factory line with machinery and equipment, possibly for predictive maintenance.

AI-supported maintenance for high plant availability

Sachsenmilch, a leading European dairy, boosts efficiency with Senseye Predictive Maintenance. Its AI/ML cloud platform proactively analyzes plant machinery, ensuring high availability, reduced maintenance, and significant cost savings. Accessible globally, it optimizes performance.

Between small profit margins, high quality standards for products that are often perishable, and tight maintenance windows between production processes, the food and beverage industry is dealing with tremendous challenges in production. Fault tolerance is therefore low. And today more and more smart, state-of-the-art networked machines are being used in production that communicate with each another and generate data – data that can, with the right software solution, be used to optimize maintenance.

Sachsenmilch Leppersdorf GmbH was founded 30 years ago and processes about 4.6 million liters of milk per day, which corresponds to 170 truck deliveries. A seamless 24/7 production process is essential for maintaining this volume. That’s why the company decided to implement a pilot product on-site in collaboration with Siemens’ Digital Enterprise Services.

A conveyor belt with milk bottles at the Sachsenmilch dairy factory.

Senseye Predictive Maintenance is a valuable addition to our existing processes in terms of preventive maintenance.

Roland Ziepel, Technical Manager, Sachsenmilch Leppersdorf GmbH

“We’re using extremely varied plant technology, but thanks to the Siemens solution, we can respond before problems develop. This greatly reduces production outages. We’ve also eliminated fixed maintenance plans: Instead, we’re guided by the condition of the plant, which also allows us to reduce maintenance costs.” One of the greatest challenges in implementing the pilot project was defining the right data for the software. “There are so many factors that play a role, including temperature, cycles, frequencies, and much more,” says Ziepel.

Siemens Senseye Predictive Maintenance solution is a platform that can identify immediate and future problems using AI-supported algorithms that have learned the normal behavior of machines and service personnel. It can be used to initiate maintenance activities before the plant actually shuts down.

The company first worked with experts from Siemens to define the right data points for predicting specific failure scenarios. Existing data from the control system was used in multiple ways. In some places, new sensors and the SIPLUS CMS1200 condition monitoring system were installed to monitor vibration.

For the entire duration of the project, Sachsenmilch benefited from the fact that Siemens not only contributed technological expertise, but also assisted with handling the project. According to Ziepel, this made the collaboration much easier. Siemens’ support for implementing the solution included the training and orientation of Sachsenmilch employees, which allowed them to quickly and successfully take over the project.

Two workers at a dairy factory inspecting the machinery.

Today we can already say that the Senseye Predictive Maintenance pilot project has paid for itself.

Roland Ziepel, Technical Manager, Sachsenmilch Leppersdorf GmbH

“For example, we were able to plan a pump replacement that resulted in a much shorter downtime compared to an unplanned pump failure during production. This action alone – the early identification of the end of the pump’s service life – saved us money in the low six figures,” says Ziepel.

The next project is already beginning. Working with Siemens, Sachsenmilch is planning to integrate Senseye Predictive Maintenance in its SAP Plant Maintenance (PM). The goal is for maintenance messages from Senseye to be automatically received by SAP PM so that they can be factored in when maintenance jobs are generated.

In the future, it will also be possible to use Maintenance Copilot Senseye more extensively as a virtual maintenance assistant that can supply data-supported recommendations for action when maintenance work is required. It consolidates all the expertise of the service team, stores all the necessary information on the plants (including machine manuals), and improves collaboration within the dairy.

Two engineers discussing the results from the Senseye Predictive Maintenance application on a large screen.