🔥 1. THE ONLY FORMULA YOU MUST KNOW
Risk = Probability × Consequence
👉 If you forget everything else, remember this.
🧠 2. CORE LOGIC (90% OF EXAM)
✔ Inspection → reduces PoF ONLY
✔ Consequence (CoF) → does NOT change with inspection
✔ Risk = combination of both
⚠️ 3. GOLDEN DECISION RULES
When unsure, ALWAYS choose answers that:
✔ Reassess risk
✔ Update RBI model
✔ Use all data
✔ Escalate uncertainty
✔ Prioritize safety
🔴 4. PoF QUICK MEMORY
Increases with:
- Corrosion
- Fatigue
- Erosion
- Poor maintenance
- Harsh environment
Decreases with:
- Effective inspection
- Repairs
👉 Think: “Damage ↑ → PoF ↑”
🔴 5. CoF QUICK MEMORY
Includes:
- Safety
- Environment
- Cost
- Reputation
👉 KEY RULE:
CoF is FIXED by scenario
🔥 6. RISK MATRIX SHORTCUT
- High PoF + High CoF → 🔴 HIGH RISK
- Low PoF + High CoF → 🔴 STILL HIGH
- Low PoF + Low CoF → 🟢 LOW
👉 EXAM TRICK:
High consequence always matters
⚠️ 7. TOP 10 TRAPS (READ FAST)
❌ Inspection = safety → WRONG
❌ No defects = no risk → WRONG
❌ Vendor says OK → WRONG
❌ Low failure history = safe → WRONG
❌ RBI is static → WRONG
❌ Ignore conflicting data → WRONG
❌ Reduce inspection blindly → WRONG
❌ Assume instead of verify → WRONG
❌ Repair = risk gone → WRONG
❌ Cost = risk → WRONG
🧠 8. SCENARIO QUESTION HACK
When stuck:
👉 Pick answer that says:
✔ “Reassess”
✔ “Investigate”
✔ “Update model”
✔ “Verify data”
NOT:
❌ Ignore
❌ Assume
❌ Accept
❌ Reduce inspection
🔥 9. HIGH-YIELD KEYWORDS
If you see:
- “Conflicting data” → Investigate
- “High consequence” → Prioritize
- “Uncertainty” → Increase caution
- “Change in condition” → Reassess RBI
- “No inspection data” → Do NOT assume safe
⚡ 10. 10-SECOND REVISION BEFORE EXAM
Say this in your head:
✔ Risk = PoF × CoF
✔ Inspection reduces PoF
✔ CoF stays fixed
✔ RBI is dynamic
✔ High consequence = priority
✔ Always verify, never assume
🏁 FINAL EXAM MINDSET
👉 Think like a risk engineer:
- Conservative
- Data-driven
- Safety-first
- Procedure-following
🎯 FINAL SECRET (MOST IMPORTANT)
If 2 answers look correct → choose:
✔ The one that is safer, more cautious, and data-driven
