Watch a reference area.
Observe repeated positions with a fixed camera and ROI.
Flowmatic CT
Select. Define.Measure. Reveal.
Flowmatic CT does not need training data, labeling, GPU inference, or a custom object model. A user selects the motion that represents the process cycle. CSRT tracking, ROI logic, and a deterministic state machine convert that motion into cycle events, Gantt charts, and abnormal-cycle evidence.
← All productsCurrent operating sequence
1 · WATCH THE REFERENCE AREA
CAMERAHOME ROI
→
2 · DETECT START / END
HOMESTARTEND00:00.0
→
3 · BUILD THE TIMELINE
LOADMACHINEUNLOADTIME12.4 s
Detect the cycle boundary.
Detect start and finish from changes in field movement.
Build time data.
Turn detected events into cycle time and a process timeline.
Product demo
Flowmatic CT working demo
Measure cycle events, Gantt timelines, and abnormal-cycle evidence without training data, labeling, GPU inference, or a custom object model.
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Measure cycle events, Gantt timelines, and abnormal-cycle evidence without training data, labeling, GPU inference, or a custom object model.
Pilot validation data
Model-free Cycle Intelligence
Measure cycle events, Gantt timelines, and abnormal-cycle evidence without training data, labeling, GPU inference, or a custom object model.
Target users
- Manufacturing engineers
- Line managers
- Improvement teams
Inputs
- User-selected Target
- CSRT Tracking
- Bird’s-eye ROI
- Deterministic State Machine
Operational events
- Cycle start
- Cycle end
- Cycle complete
- Variation review candidate
Outputs
- Cycle Event
- Gantt
- Abnormal-cycle Evidence
Pilot conditions
- Fixed camera position
- Verifiable ROI
- Lighting and view-change check
- Prior agreement on video storage and retention
KPI candidates
- Automatic measurement coverage
- Manual recording time
- Cycle variation range
- Abnormal events requiring review
Pilot scope: One work position or machine · one repeated process