The rollers of the sorter carriers are monitored by stationary sensors to detect wear. This can be recognized by unbalanced movements and deviations in carrier height. Sensors also check the vibrations and evenness of the sorter tracks, as well as forces acting upon the chain.
Why service processes are so essential
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. By shifting from time-based maintenance models to predictive maintenance, you can effectively optimize your overall process and use your resources sparingly.
Benefits at a glance
- Operational downtimes averted or significantly reduced
- Minimized operational risk through predictive analysis and better visibility into system health
- Enabling of predictive and optimized maintenance, as well as material and resource planning
- Extended system service life through condition monitoring, data-based analysis and system component optimization
- Increased occupational safety, as maintenance work with special safety requirements, such as working at heights, is reduced
- Monitoring of many components of different systems – also from third-party suppliers
SmartService – digitalization makes it possible
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. When comparing with the current values, statements about the condition can be made. The results are used to predict the best time to perform necessary maintenance and 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.
Innovative technology optimizes the service processes
Condition data from sensors is preprocessed through edge computing. The results are sent via a secure connection to MindSphere – Siemens' 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 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.
Our SmartService portfolio improves and optimizes your service processes
Benefit from our innovative and digital condition monitoring solutions.
Service 4.0 from Siemens Logistics enables airports to collect and evaluate data for the predictive maintenance of their baggage handling systems. To further improve operational processes, going forward Siemens will equip drives with innovative edge technologies from the company’s Digital Industries unit. Thanks to additional detailed information, this smart solution will enable wear to be detected earlier than before – such as on VarioTray TilterPlus. Unexpected downtime can be avoided.
The result is a considerably improved predictive maintenance approach. Customers benefit from optimal system availability and capacity, extended baggage handling system lifetime and lower operating costs.