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| Criterion |  Engineering Fault Isolation |  Knowledge Modeling Knowledge Mapping |  Operations Root Cause Analysis |  Engineering Hypothesis-Driven Troubleshooting |
|---|---|---|---|---|
Purposedifferent | In technical failures, the visible symptom often gets mixed up with the actual cause. Fault Isolation narrows the fault space and progressively reduces which part of the system is truly affected. | Knowledge Mapping makes knowledge, gaps, and transfer paths visible across a field. It fits when expertise should not just exist but also be findable and transferable. | When a problem keeps recurring and the cause stays unclear, the method exposes the underlying mechanism. It separates symptom, guess, and robust explanation from one another. | When systems fail unexpectedly, spontaneous attempts often produce more noise than insight. Hypothesis-driven Troubleshooting translates symptoms into testable assumptions and makes troubleshooting learnable. |
Complexitysame | Medium | Medium | Medium | Medium |
Timedifferent | 30-180 min | 1-3 h | 1-4 h | 30-240 min |
Participantsdifferent | 1-6 | 3-12 | 3-8 | 1-6 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop + async |
Outputdifferent | Fault Isolation Map, Test Log, Excluded Hypotheses, Narrowed Fault Area | Knowledge Map, Critical Knowledge Areas, Transfer Plan | Problem Statement, Cause Hypotheses, Confirmed Causes, Action Plan | Hypothesis Log, Test Plan, Evidence Notes, Diagnosis Summary |
Tagsno overlap | TroubleshootingDiagnosisEngineering | KnowledgeMappingRisk | Root causeProblem solvingQualityIncident | TroubleshootingProblem solvingDiagnosis |