PdM, CBM, APM, xDT, Process Optimization with Edge Streaming Analytics (SAS)
Experts working along the value chain are nowadays confronted with high productivity and decision-making pressure. Machine operators need real-time feedback for anomaly detection to support decisions that can affect line availability, product quality, and therefore product throughput. Subject matter experts need a way to implement their analytic concepts to drive line improvements by flexible data connection and predictive modeling. Fleet engineers, who need to understand similar machines across a large fleet, leverage learnings to improve performance and provide feedback to machine designers.
Edge Streaming Analytics provides users with a cloud-based UI for project creation and management. Its built-in analytics with drag & drop programming and low latency analytic execution on edge devices of choice enables process optimization.
The solution helps to reduce downtime in production up to 70% and allows a reduction of up to 25% in repair time as well as up to 10% in maintenance costs. All this with a closed-loop development of analytics from MindSphere to Open Edge.
- Access to data sources/streams in standard industry protocols
- Edge device such as Siemens IPC or equivalent with a 64-bit processor and 2GB RAM minimum
- Subject matter experts use an intuitive drag & drop interface and data scientists may use programming interfaces
- Online & in-person training options as well as documentation are available
- Confirmation of business value with help of Use Case Screening and Data Readiness Check as well as Proof of Value
- The implementation takes place after Edge and Cloud connection testing and application refinement with tailored interface for operators
- After the initial use of the solution first experiences are evaluated, outputs and interfaces are verified and the business benefit is stated
- To ensure effective use of the application regular cadence is monitored