Cost of Breakdown OR Cost of Care: How Much Inspection or Maintenance is Enough?

Agentic Asset Strategy Engine

How six diagnostic measures over SAP FSM history produce an asset health score and shift inspection and maintenance from fixed calendars to condition-based intervals.

Chapters

  1. ONE CRITICAL QUESTION: Every inspection and maintenance plan answers one question. How much inspection or maintenance? Too little, and the asset breaks. Too much, and you pay for nothing found.
  2. THE COST OF GUESSING: Most intervals are still a calendar guess. Every 90 days. Because it has always been 90 days. The asset never agreed to that number. Its own history says something different.
  3. THE FUEL — SAP FSM: The evidence is already in the field service system. Equipment, with its classes and custom fields. Notifications — the event stream, priorities, breakdown flags. Closures — damage and cause, written by the technician. Nothing new to install. Only history, read properly.
  4. THE PIPELINE: Raw history in. A six-pillar diagnostic engine. A cohort health score, 0 to 100. A proposed interval, in days. Optionally written straight back to SAP PM.
  5. THREE CLOCKS: Assets do not all age on the same clock. Calendar time — for steady-state, unmonitored assets. Counters — hours and cycles, for usage-driven wear. Live condition — vibration, temperature, from measuring points. Condition always overrules the calendar.
  6. THE SIX-CYLINDER ENGINE: Six measures, mixed into one score. Looking back — yield, and fault clustering. Looking forward — Weibull, and risk-based inspection. Reality checks — the P-F interval, and confidence. Higher score, extend. Lower score, shorten.
  7. YIELD: Yield asks what the last visits actually found. Mostly nothing? You are inspecting too often. Breakdowns between visits? Too rarely. The findings rate is the first honest signal.
  8. CLUSTERING: Then the engine pairs damage with cause. Seal leak / wear. Bearing noise / misalignment. The same fault, again and again, is the asset repeating itself until you listen.
  9. WEIBULL & THE BATHTUB: From the gaps between notifications, a Weibull fit. β < 1 — infant mortality. Installation, parts, start-up. β ≈ 1 — random. Intervals barely help; redesign does. β > 1 — wear-out. Predictable, and optimisable. The bathtub curve, fitted per asset cohort. β shape, η characteristic life.
  10. THE P-F INTERVAL: Failure is rarely instant. P — the first detectable symptom. F — functional failure. The window between them is the only time you have. A regression on live readings projects remaining life, and the interval is set well inside that window.
  11. RISK & CONFIDENCE: Two modifiers keep the maths honest. Risk — high-priority cohorts are pulled to shorter intervals. Confidence — thin or noisy data is damped toward neutral. Below 0.4 confidence, no extension is allowed.
  12. HIDDEN MODES: One fit per cohort hides the dangerous case. So each failure mode gets its own Weibull. damage × cause × part A healthy average can conceal one mode racing to failure.
  13. WHEN REALITY DISAGREES: An asset breaks earlier than the statistics allow. The engine opens a root cause analysis by itself, recording predicted days against actual days. Fishbone and five-whys become a new FMEA mode, and its severity flows back into the score.
  14. THE ASSET HEALTH INDEX: Everything compiles into one number. Start at 50. Add yield. Adjust for the Weibull regime. Subtract for P-F alarms, open RCAs, critical FMEA modes. Then damp the whole thing by confidence. One score the planner can defend.
  15. FROM SCORE TO ACTION: The score becomes a proposal, not a report. Under 30 — halve the interval. 45 to 64 — hold. 80 and above — double it. Every proposal arrives with its rationale.
  16. THE CLOSED LOOP: Each closure feeds the next fit. Each breakdown sharpens the next prediction. The strategy stops being a document and becomes a system that learns.
  17. THE SHIFT: From time-based inspection and maintenance — fixed calendars, uniform intervals, hope. To smart, data-driven, condition-based strategy — each asset inspected and maintained on its own evidence. Same technicians. Same system. Better questions answered.
  18. WHAT IT BUYS YOU: Maximise uptime — shorten intervals on deteriorating assets before they fail. Optimise labour — safely extend intervals on proven-reliable equipment. Automated rigor — a self-learning, damped engine instead of calendar guessing. Industry studies put predictive strategies at roughly 30–50% less downtime and 20–40% longer asset life (McKinsey). Fewer no-finding visits. Fewer surprises.
  19. CLOSURE: Cost of Breakdown OR Cost of Care. Your FSM data, finally answering the question. Your data beyond dashboards and displays: Get actionable insight.

Cost of Breakdown OR Cost of Care: How Much Inspection or Maintenance is Enough?

Please enter your email address before accessing the page. Your data is used for verification purposes and is not used for any other purpose nor is shared with any other party.