As a logistics systems operator, you need your equipment to work reliably whenever it is needed. With our Service 4.0 approach, unplanned downtimes and emergency maintenance are a thing of the past.
We are continually enhancing our predictive maintenance solutions. Our SmartService portfolio monitors the components of a wide range of systems, including third-party solutions. Although standardized solutions are on offer, your individual requirements are always at the heart of how we act and think as partners.
The basis for predictive maintenance is condition monitoring, which uses artificial intelligence to identify patterns in historical sensor data. The results are used to predict the best time to perform necessary maintenance and to predict the service life of a component. With our SmartService portfolio, you benefit from optimized maintenance scheduling and execution with just-in-time measures. You can realize higher operational availability, greater efficiency and productivity, and boost competitiveness.
Condition data from sensors is preprocessed through edge computing. The results are sent via a secure connection to MindSphere – Körber' open IoT cloud-based operating system – for further analysis. Tools such as machine learning, pattern recognition, and trend determination analyze the data and calculate the best time to perform maintenance work.
The results are displayed on asset and analysis dashboards. Service teams use the details to call up recommended courses of action for necessary measures. These are then performed at the optimum time and not merely according to the maintenance schedule, which might indeed be too early or late.