The innovative approach for higher efficiency and reliability
Operators of material handling and logistics systems need to ensure that their facilities are available when needed. Unplanned downtime and emergency maintenance are major challenges. By transitioning from time-based service models to predictive maintenance, companies can effectively optimize their processes as a whole.
SmartService – tested and proven portfolio
Siemens Logistics is continuously developing the solutions for predictive maintenance that have proven themselves in the field. The product range includes critical components of various systems – also from third-party providers.
The basis for predictive maintenance is a condition-based approach that uses artificial intelligence to recognize patterns in historic sensor data. The results are used among others to forecast the best time to perform maintenance, or to predict a wear part’s end of life. With Siemens Logistics’ SmartService portfolio, customers benefit from optimized maintenance planning and execution with just-in-time equipment servicing. Higher levels of operational availability are achieved along with increased efficiency, productivity and competitiveness.
Analytics and visualization
As a first step, condition data from various sensors is pre-processed on an edge device. The data are then transferred via secure channels to MindSphere, Siemens’ open IoT cloud-based operating system, for advanced analytics. Tools such as machine learning, pattern recognition and trend identification are used to analyze the condition data to determine the best time to perform maintenance.
Results from each supervised resource are displayed on dashboards in two views – asset and analytics. Based on those illustrated details service teams get information about recommended actions.
- Reliability and availability: Operational downtime is significantly reduced or eliminated, and operational risk is minimized through predictive analytics and transparency of the system condition
- Efficiency: By planning maintenance activities according to the assets’ conditions, unnecessary work is reduced and/or eliminated
- Effectiveness: SmartService enables predictive maintenance, material and resource planning as well as focused execution of maintenance activities in an optimized manner
- Asset optimization: The useful lifetime of assets is extended through data-driven root-cause analysis and equipment optimization
- Safety: Workplace safety is improved by reducing maintenance activities that have special safety requirements, such as working in heights
- Versatile use: Sensors monitor different critical components of various systems – also from third party suppliers