Avionics Test Failure Analysis Assistant
Diagnose complex avionics failures by correlating test data and building decision trees
What You Can Do
You can analyze complex avionics test failures by feeding Claude multiple data streams—oscilloscope traces, BITE logs, CAN/ARINC 429 transcripts, and environmental parameters—to build diagnostic decision trees that prioritize root causes based on failure signatures. Claude helps you cross-reference specifications against observed behavior, identify design-versus-implementation gaps, and generate testable hypotheses with step-by-step verification procedures that accelerate failure resolution across multi-LRU (Line Replaceable Unit) systems.
Features
oscilloscope traces, BITE logs, CAN/ARINC 429 transcripts, environmental telemetry, and lab equipment readings into unified failure narrative
prioritize high-probability root causes by analyzing failure signatures and symptom patterns across integrated avionics systems
identify gaps between design requirements, implementation, and observed behavior to pinpoint design defects or configuration issues
create step-by-step verification procedures with specific test conditions and success criteria for rapid hypothesis validation
create traceable root cause narratives for trend analysis, design defect tracking, and recurring failure prevention
correlate multi-system data to identify timing dependencies, transient conditions, and race conditions in integrated avionics
apply structured diagnostic methodology to challenge assumptions and explore non-obvious failure paths
rank next-step investigations by likelihood and impact to minimize test iterations and hardware cycles
Example Output
Example 1: Multi-LRU Intermittent Failure
Input: Oscilloscope traces showing ARINC 429 bus dropout, BITE logs indicating autopilot mode annunciation failures, IRS health monitoring flags.
Output:
- Failure Signature: ARINC 429 line A dropout correlates with 50ms power transient on IRS LRU
- Diagnostic Tree: Primary suspect = IRS power supply ripple causing transceiver lockout → Secondary suspect = autopilot software timeout logic → Tertiary suspect = shielding deficiency in main deck harness
- Testable Hypothesis: "IRS LRU exhibits inadequate power supply filtering under dynamic load. Verification: measure rail ripple during autopilot mode transitions; if >200mV peak, replace capacitor bank C47-C52."
Example 2: Design-vs-Implementation Gap
Input: Flight control computer test data showing elevator command lag, specification sheet stating max response time 150ms.
Output:
- Root Cause Identified: Flight control law revision 2.3 added adaptive filtering not documented in interface control document (ICD); filter time constant = 220ms
- Verification Steps: (1) Compare loaded firmware version hash against ICD baseline, (2) Extract control law gain schedule from core dump, (3) Run closed-loop sim with firmware coefficients
- Resolution Path: Update ICD revision 3.1 or revert flight control law to revision 2.1 pending certification review
What's Included
- SKILL.md: Core instruction file with structured failure analysis methodology and decision tree framework
- Diagnostic Template: Data aggregation worksheet for organizing oscilloscope traces, BITE logs, CAN transcripts, and environmental parameters
- Decision Tree Canvas: Structured format for mapping failure symptoms to root causes with probability weighting and cross-references to specification requirements
- Hypothesis Verification Checklist: Step-by-step test procedure template with pass/fail criteria, measurement thresholds, and next-action logic
- Failure Chain Documentation: Root cause narrative template for recording investigation timeline, ruling-out sequence, and design defect tracking
Who It's For
- Avionics Test Engineers — troubleshooting complex multi-system failures and accelerating root cause identification
- Flight Systems Integration Engineers — diagnosing design-versus-implementation gaps across integrated avionics architectures
- Field Service Engineers — rapidly resolving customer aircraft failures with limited access to hardware and multiple data streams
- Quality and Reliability Engineers — documenting failure chains for trend analysis and preventing recurring defects
- Systems Safety Engineers — investigating failures that span multiple LRUs and have potential airworthiness implications
Best For
- Intermittent avionics failures that are difficult to reproduce and require multi-source correlation
- Multi-LRU failures spanning flight control, navigation, and communication systems
- Failures that appear to violate specification requirements or design assumptions
- Complex troubleshooting that has exceeded 2+ hours of manual analysis without resolution
- Design defect investigations requiring cross-reference of specifications against implementation
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