Context: Overall Equipment Effectiveness is a core manufacturing KPI because it reflects how reliably execution decisions are made while the line is running, not whether machines lack capability.

Challenges: Availability losses are acknowledged after the shift, speed degradation becomes tolerated rather than corrected, and quality drift is logged but not interrupted. Responsibility spans production, maintenance, and quality, so by the time performance is reviewed, the opportunity to recover minutes is gone.

Solution: The OEE Guidance Agent, an AI agent built using Microsoft Copilot Studio, monitors availability, speed, and quality signals as the line runs and intervenes during shift handover and loss-type identification, flagging the corrective action before performance slips further.

Impact: Manufacturers adopting this approach see losses acted on while the line is still running rather than explained after the shift ends, with OEE rising not because reporting improves, but because execution responds in time to keep performance stable throughout the day.