Context: In mining operations, equipment downtime percentage reflects how well risk is contained while assets are operating, not simply a measure of mechanical reliability.

Challenges: Minor performance degradation, repeated interruptions, and deferred maintenance signals appear well in advance, yet action is postponed while approvals are sought or responsibilities shift between teams.

Solution: The Downtime Prevention Guidance Agent, an AI agent built using Microsoft Copilot Studio, monitors operating conditions as they move out of tolerance and intervenes during maintenance prioritization and load reduction decisions, flagging emerging risk while the line is still running.

Impact: Mining operators following this approach see teams act before degradation becomes disruption, with uptime stabilizing because execution responds in time while control is still possible.