Siemens Logistics has launched its latest service product, SmartService, which it says will help parcel centers minimize costly system downtimes and substantially improve system availability.
A key element of the service approach, the company says, is predictive maintenance. Collected data helps detect changes in the condition of systems and their components at an early stage. This means necessary measures such as service, repair and simple cleaning are carried out at the optimum time and resources are used efficiently.
The company says the approach is based on condition monitoring of the systems, in which mobile and stationary sensors record, for example, vibration and distance measurements of rails and belts as well as forces on chains. If deviations from threshold values established from historical data analysis are identified, customers can plan and carry out targeted maintenance measures and thus avoid downtimes.
Smart applications and machine learning algorithms evaluate collected data and predict the remaining life of components, such as sorter carriers, belts and motors. To store and analyze the data obtained, Siemens offers the open, cloud-based IoT operating system MindSphere.
Siemens Logistics notes it has already implemented SmartService solutions such as Sorter 360 and Motor 360 in the parcel sector. In the case of Sorter 360, this provides customers with data indicating, for example, the degree of wear and tear on sorter carrier rollers. This is achieved by monitoring the vibration and height of moving parts on tilt-tray sorters, such as on crossbelt sorters, like the VarioSort EXB, in parcel sorting centers. Installation is also possible on third-party sorters.
Motor 360, meanwhile, focuses on recording and evaluating data that already exists in the system, enabling abnormal current values to be identified in good time.