Published 7 October 2026, Updated 7 October 2026
16. Risk Heatmap
Risk Heatmap compares pilot-squawk rates per 100 flight hours with the median for aircraft of the same type. It is designed to reveal unusual patterns after adjusting for utilization.
- Select the date range.
- Select ALL or one or more resource types.
- Select Filter!.
- Review the fixed context columns and then the system-tag cells.
[SCREENSHOT: maintenance-risk-heatmap-filter | Capture: Date range, multi-select resource types, Filter button, and legend.]
16.1 Read the table
| Column/cell | Meaning |
|---|---|
| Resource Type / Registration | Aircraft being compared within its type. |
| First Activity / Last Activity | Activity coverage in the selected period. |
| Total flight hours | Exposure used to normalize the rate. |
| Max Δ% | Worst deviation for that aircraft across displayed tags. |
| Tag cell | Percentage deviation for that system tag; a dash means no comparable result. |
| Background color | Fewer or more squawks than typical for the same aircraft type. |
| Up/down trend marker | Worsening or improving trend. |
| Abnormal marker | A newly emerging deviation. |
Hover a tag cell to see status, deviation, rate per 100 flight hours, type median, squawk count, comparison span, new-deviation status, and trend interpretation.
[SCREENSHOT: maintenance-risk-heatmap-table | Capture: Heatmap with context columns, several tag cells, legend, worsening/improving markers, and an abnormal marker.]
[SCREENSHOT: maintenance-risk-heatmap-tooltip | Capture: One cell tooltip showing deviation, rate/100FH, type median, count, comparison span, and trend.]
16.2 Use the heatmap responsibly
The heatmap identifies where review may be valuable; it does not confirm a defect. Consider:
- Flight hours and number of squawks
- Whether the comparison period is representative
- Quality and consistency of pilot reporting
- Recent maintenance or operational changes
- The individual descriptions and technical findings
Use a worsening or new deviation to prioritize inspection and monitoring, not to replace an approved troubleshooting or release process.
17. AI tab
When enabled and authorized, the AI tab presents a Weekly Aircraft Maintenance Reliability Assessment derived from statistically prepared pilot-squawk and flight-hour information.
The report is decision support only. It does not alter the underlying records and does not replace approved maintenance procedures, regulatory records, inspection findings, or authorized judgment.
[SCREENSHOT: maintenance-ai-overview | Capture: AI tab title, decision-support warning, and the complete weekly report area.]
17.1 Fleet overview, Trend analysis, and Summary
- Fleet overview shows related aircraft, related systems, alerts, critical items, and new deviations.
- Trend analysis counts worsening, improving, and stable systems and may include commentary.
- Summary states the report period, overall risk level, and key message.
Check the report period and limitations before using any count. Low hours, inactivity, or missing information can reduce confidence without implying a defect.
[SCREENSHOT: maintenance-ai-summary | Capture: Fleet overview KPIs, Trend analysis, Summary period, risk level, and key message.]
17.2 Maintenance priorities and Limitations
Maintenance priorities lists focus areas with supporting rationale. Limitations identifies constraints on the analysis. Review limitations first when a recommendation seems surprising or conflicts with operational knowledge.
[SCREENSHOT: maintenance-ai-priorities-limitations | Capture: Maintenance priorities and Limitations sections with multiple entries.]
17.3 Aircraft findings
Each aircraft finding can show:
- Overall status
- Registration and type
- System tag
- Severity
- Trend
- NEW marker
- Suggested action such as inspect, schedule maintenance, or immediate attention
- Plain-language maintenance interpretation
Treat the suggested action as a prompt for authorized review. Open the original squawks, compare current status, and record the actual disposition in the proper maintenance records.
[SCREENSHOT: maintenance-ai-aircraft-findings | Capture: Aircraft findings showing severity, trend, NEW marker, suggested action, and interpretation.]
17.4 Systemic patterns
Systemic patterns identify recurring fleet-wide tags, affected-aircraft count, description, possible causes, and suggested fleet action. Validate common reporting practices and aircraft-type differences before treating a pattern as common cause.
[SCREENSHOT: maintenance-ai-systemic-patterns | Capture: Systemic pattern with affected-aircraft count, description, possible causes, and fleet action.]