AI CopilotInsights from marked events — weak links, prevention gaps, and cost performance
Assets analysed
P1 prevention opportunities
Downtime — total recorded
Cost overrun — over-budget WOs
Asset risk ranking — weak links
Which assets need attention?
Scored on P1 events, downtime hours, marked findings and open work. Hover a row to review or dismiss.
Prevention opportunities
Could these failures have been avoided?
Events where maintenance strategy gaps contributed to the failure
Cost performance — budget overruns
Which work orders exceeded budget?
Ranked by percentage over planned cost
Downtime follow-up queue
Events to investigate for root cause
Sorted by downtime hours — largest impact first
Reliability issues
Dates not honored
Events where planned or due dates were missed — directly impacts reliability metrics
Data quality & inspection
Data integrity and over-inspection findings
Data errors reduce asset metric reliability — over-inspection wastes PM capacity
All readings normal — consider reducing inspection frequency
Key takeaways for management
Summary of findings requiring prioritisation
7 work orders were marked as P1 prevention opportunities — 2 failure modes had no PM plan, 5 had an interval that was too long. Review PM scope and inspection frequencies.
7 preventable failures identified — 2 failure modes not covered by any PM plan, 5 events where warning signs preceded the failure. Review PM scope and intervals.
45.0 h total downtime — HX-101 (18.0 h) and MOT-402 (9.0 h) are the largest contributors. Root cause investigation recommended.
Cost estimating accuracy is low — overruns average +11% across 6 work orders. Review scope definition and cost estimation process.
2 data quality issues found — wrong tag bookings distort per-asset reliability metrics and maintenance history. Correct before next reporting cycle.
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