Situation:
- IoT platforms improve efficient data streaming from operation and service of machine fleets. The machine life-cycle becomes transparent
- Remote connections to machines inherit security and accessibility risks
streamwise solution
- streamwise has developed a nonintrusive operation monitor “attached monitor” that detects basic machine operation patterns like start/stop or load based on emission signatures
- This allows us to connect operation with fleet service data and developed a fleet service monitor
- We establish nonintrusive fleet surveillance with machine learning algorithms to evaluate equivalent operation hours (EOH) and adapt service execution
- Our service prediction models base on real fleet operation data and drives inventory and delivery execution
- We apply our solution on Siemens Mindsphere and Microsoft Azure platforms