8069d0ea89543d6353c5c7425a9bbfac62102721
7 Commits
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8069d0ea89 |
fix(iace): assign mitigations to ALL hazards per category
hazardIDsByCategory changed from map[string]uuid.UUID to map[string][]uuid.UUID — measures are now distributed to every hazard in a category, not just the last one created. Previously 94/108 hazards had no measures, now all get them. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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cca714755a |
fix(iace): stronger relevance filter + matcher wrong-machine penalty
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Relevance filter: now checks PatternName in addition to ZoneDE+ScenarioDE, catches "Spielplatz", "Umreifungsband", "Fahrtreppe" etc. in pattern names. Added more generic safety terms to whitelist (welle, getriebe, kette, etc.) Matcher: rebalanced weights (category 0.3, keywords 0.3, zone 0.4) to prioritize zone/component specificity. Added wrong-machine penalty (0.3x) when engine hazard mentions machine-specific terms absent from GT context (e.g. "Kollision zweier Roboter" for a single-robot GT entry). Fixes 18 problematic matches: 8 wrong-machine, 9 zone-mismatch, 1 category. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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733d2bcc7b |
feat(iace): per-category hazard caps for precision improvement
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Add categoryHazardCap() with ISO 12100-proportional limits: - mechanical: 3x components (min 15, max 60) - electrical: 1x components (min 8, max 20) - secondary (thermal, noise, material): 4-8 - software/IT/organizational: 2-5 (minimal for machinery assessment) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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be2ac762bd |
feat(iace): narrative vocabulary overlap filter replaces blacklist
Replace machine-specific term blacklist with generic vocabulary overlap: - Extract significant words (>=5 chars, not generic safety terms) from pattern zone/scenario - If pattern has specific words but NONE appear in narrative → filter - genericSafetyTerms whitelist with ~50 terms that appear in all assessments - Truly generic approach: works for any machine type without maintenance Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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1bd892afbf |
feat(iace): narrative relevance filter + zone normalization for precision
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- isPatternRelevant() filters patterns whose zone/scenario mentions machine-specific terms (extruder, stanzpresse, spielplatz, etc.) absent from the actual machine narrative - normalizeZoneKey() clusters similar zones for smarter dedup (e.g. "Schaltschrank, Sammelschiene" = "Schaltschrank-Innenraum") - machineSpecificTerms list with 40+ terms for generic filtering Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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8bb90d73e5 |
feat(iace): benchmark system + erklaerteil + dedup-fix
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- Erklaerteil-Template fuer Risikobeurteilungen (risk_assessment_template.go) in PDF-Export, Markdown-Export und Frontend ReportPrintView eingebaut - Ground Truth Benchmark-System: Datenmodell, Fuzzy-Matching-Engine, 3 API Endpoints (import-gt, benchmark, benchmark/summary) - Frontend Benchmark-Tab mit Score-Cards, Kategorie-Breakdown, Hazard-Vergleichstabelle (Zugeordnet/Fehlend/Extra), Business Impact - Erster Benchmark: 13.3% Coverage (Baseline) gegen 60 GT-Eintraege - Dedup-Fix: seenCat[cat] -> seenCatZone[cat+zone] erlaubt mehrere Gefaehrdungen pro Kategorie an verschiedenen Gefahrenstellen - Komponenten-spezifische Hazard-Namen und Zone-basierte Zuordnung Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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f5664612ad |
feat(iace): Einsatzbereich / Branche — filtert branchenspezifische Patterns
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Neues Feld "Einsatzbereich" auf Interview-Seite (Sektion 7) mit 15 Branchen. Pattern Engine bekommt MachineTypes aus MatchInput → branchenfremde Patterns (Medizin, Aufzug, Bau etc.) feuern nur wenn die Branche ausgewählt ist. Refactoring: iace_handler_init.go aufgeteilt in init + init_helpers (LOC-Limit). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |