Plant managers and process engineers see an overall OEE number on a dashboard but cannot quickly determine whether a drop was driven by availability losses, performance rate degradation, or quality rejections - and on which line or shift it occurred. The data exists across MES, historian, and downtime tracking systems, but pulling it together for a shift debrief takes hours of manual report-building that nobody has time for.
Built For
Process Engineer or Production Supervisor responsible for OEE improvement targets across one or more production lines in a discrete or process manufacturing environment
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Process Engineer
Optimizes OEE across availability, performance, and quality factors. Identifies micro-stops and bottleneck patterns.
Maintenance & Reliability
Correlates availability losses to equipment downtime events and maintenance history.
Quality Engineer
Tracks quality loss contributions to OEE and links rejection events to process parameter deviations.
Decompose OEE into availability, performance, and quality factors across lines and shifts through natural language queries. Identify bottlenecks, track micro-stops, and correlate downtime codes to root causes in seconds.
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Defect rates spike by 40% during the shift handover period (2pm-3pm). There is also a strong correlation with 'Line 3' speed settings above 80%.
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