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| Criterion |  Engineering Hypothesis-Driven Troubleshooting |  Knowledge Modeling Knowledge Mapping |  Operations Fault Tree Analysis |  Operations 5 Whys |
|---|---|---|---|---|
Purposedifferent | When systems fail unexpectedly, spontaneous attempts often produce more noise than insight. Hypothesis-driven Troubleshooting translates symptoms into testable assumptions and makes troubleshooting learnable. | 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. | For a critical top event with several possible triggers, the method logically models failure paths. It makes visible which combinations of conditions can lead to damage. | For a single, hard-to-explain deviation, the method exposes the causal chain behind the visible symptom. It keeps the cause open until a controllable condition emerges instead of a mere description. |
Complexitydifferent | Medium | Medium | High | Low |
Timedifferent | 30-240 min | 1-3 h | 2-6 h | 15-30 min |
Participantsdifferent | 1-6 | 3-12 | 3-8 | 2-6 |
Formatdifferent | Workshop + async | Workshop | Workshop + async | Workshop |
Outputdifferent | Hypothesis Log, Test Plan, Evidence Notes, Diagnosis Summary | Knowledge Map, Critical Knowledge Areas, Transfer Plan | Fault Tree, Critical Paths, Cause Hypotheses, Control Actions | Root cause notes, Countermeasures |
Tagsno overlap | TroubleshootingProblem solvingDiagnosis | KnowledgeMappingRisk | RiskRoot causeSafety | Root causeIncidentLeanProblem solving |