The example of the customer Münzing Chemie GmbH shows how production optimization using BCAP (Bilfinger Connected Asset Performance) can be carried out solely on the basis of sensor data while maintaining full plant availability. The project started at the beginning of 2019 and demonstrates how batch output in the powder additive plant can be increased using the Recommender Model and the Virtual Sensor. Bilfinger is working together with Münzing Chemie GmbH as a full-service provider.
|Name:||Münzing Chemie GmbH|
|Focus:||Mixing plant for construction additives|
Münzing Chemie GmbH wanted to increase production in its powder additive plant. In the plant, the chemical raw material is applied in liquid form to a silicate and thus solidified into a powder. It was important to avoid any interruption of production that could become necessary due to a physical adjustment of the powder additive plant. The optimization of the production process was therefore based solely on data obtained. Achievement of the optimization goals was to be measured by the increase in the batch output of the powder additive plant.
The optimization of the production process, however, was not only intended to reduce mixing times. Other objectives included improved preparation times, such as earlier possible preparation of the next batch production, together with optimized cleaning of the plant.
„The Recommender Model fully met our expectations: It was possible to achieve the optimization solely on the basis of sensor data and without any intervention in the existing plant. The increase in production capacity with identical product quality is a clear benefit for Münzing Chemie GmbH.“
Sven Scholz , Plant Manager, Münzing Chemie GmbH
Münzing Chemie GmbH succeeded in optimizing production while maintaining quality using the Recommender Model. The sum of the shortened mixing times results in an additional daily batch of output. The time gained can also be used for maintenance or cleaning processes. This means that a significant increase in production was achieved without the need for physical modifications to the powder additive plant. Plant availability was also ensured during the optimization phase. The Virtual Sensor made it possible to generate reliable predictions of product quality in real time. This eliminates the need for time-consuming sampling and analysis in the laboratory, and quality can be monitored directly.
The user benefits from other advantages, such as the visual display of all process-relevant information in a dashboard. With the dashboard, the operator has a tool at his disposal that allows him to optimize mixing times. Feedback from the plant operators via the dashboard also supports the optimization processes.
As a further benefit, the vibration sensor provides data that can be used for smart alerting, condition monitoring and predictive maintenance.