Most plants find out what happened at shift end.
Manufacturing floors generate data constantly, but most operations still run on end-of-shift summaries and verbal handoffs. Downtime gets discovered late. Quality issues are found downstream of where they started. Throughput numbers come from whatever the last operator wrote down.
By the time a problem shows up in a report, the window to fix it is already closed.
A live view of what's happening on the floor.
Built on actual equipment data.
We build production monitoring systems that connect directly to your PLCs, sensors, and existing historian or MES data — and surface OEE, throughput, downtime events, and quality metrics in real time.
Operators see what's happening now. Supervisors see where output is degrading. Engineering sees the patterns behind recurring losses.
How it runs.
Data ingested
PLCs, sensors, and historian/MES data connected via OPC-UA, MQTT, or direct API. No manual entry required.
Events detected
System identifies stoppages, slowdowns, speed losses, and quality deviations in real time as they occur.
Context added
Events tagged with line, cell, shift, product, and operator — so data is useful, not just voluminous.
Alerts sent
Floor operators and supervisors notified based on severity, escalation rules, and response time thresholds.
Downtime classified
Stoppages categorized by reason code. Patterns become visible across shifts, lines, and equipment.
Reports generated
OEE, throughput, and quality trends available by shift, line, and product — automatically, not manually compiled.
What gets built.
Data Layer
- OPC-UA / MQTT connectors
- Historian & MES integration
- ERP production order sync
- Custom PLC data extraction
Monitoring Engine
- Real-time event detection
- OEE calculation (availability, performance, quality)
- Downtime reason code classification
- Shift and product context tagging
Operational Layer
- Live floor dashboards
- Supervisor and executive views
- Shift summary reports
- Alert configuration and escalation
What changes when this runs.
Downtime identified in real time, not discovered at shift end
OEE becomes measurable and improvable instead of estimated
Quality escapes caught earlier before they compound downstream
Shift handoffs backed by actual data rather than verbal summaries
Engineering and operations share the same view of what's happening
Recurring loss patterns become visible and addressable for the first time
Foundation for predictive maintenance and production optimization.
Real-time monitoring is the first layer. Once equipment data is connected and baselines are established, the same infrastructure supports condition-based maintenance, anomaly detection, and AI-driven recommendations.
It starts with knowing what's happening. Everything else follows from there.
Running a manufacturing operation?
Tell us what your floor looks like today and where you're flying blind. We'll map out how to get real-time visibility into it.