Reactive vs preventive vs predictive maintenance — explained for plants

Three types in plain language

Manufacturing maintenance usually falls into three buckets. The labels get marketed heavily; the floor definitions stay simple.

• Reactive (run-to-failure or break-fix) — you repair after the asset fails or a fault forces a stop. Speed and history quality decide how painful it is.
• Preventive — you perform planned work on a time, usage, or event trigger before expected failure (inspections, replacements, lubrication, calibrations).
• Predictive — you watch condition signals (vibration, temperature, current, vision/quality proxies, process alarms) and intervene when risk rises, ideally closer to actual need than a fixed calendar.

All three can coexist. Maturity is about sequencing, not replacing reactive work overnight.

Comparison: cost, data needs, failure mode fit

Reactive

• Cost profile: low planning cost; high and unpredictable downtime cost on critical assets
• Data needs: work-order capture and restore timing
• Fits: non-critical assets, cheap failure modes, or failures you cannot economically predict yet

Preventive

• Cost profile: planned labor and parts; pays off when it prevents expensive stops
• Data needs: asset schedule, windows, checklists, completion history
• Fits: wear-out and interval-driven failure modes with known windows

Predictive

• Cost profile: sensors, analytics, and analyst attention — plus the work those alerts create
• Data needs: reliable signals and an execution path (owned work, parts, history)
• Fits: critical assets with detectable precursors and a crew that will act on alerts

If you only remember one contrast: preventive asks “is it due?” Predictive asks “is risk rising?” Reactive asks “what just broke?”

When reactive is still rational

Reactive is not always a failure of professionalism.

Use deliberate run-to-failure when:

• The asset is non-critical and failure is cheap to restore
• Redundancy exists and a stop does not halt the line
• You lack a credible precursor signal and PM would cost more than the failure
• You are still building history and need to capture failures cleanly first

The problem is accidental reactive on critical machines — no history, no ownership, no learning. Capture reactive work well even while you grow PM. That history is how you choose what deserves preventive or predictive spend.

Building preventive without theater

Preventive programs fail when they are calendar-perfect and window-blind.

Do this instead:

1. Start with critical assets and known repeat failure modes
2. Use a short [PM schedule template](/guides/preventive-maintenance-template) with real production windows
3. Convert due PM into owned work orders
4. Measure finish rate, not binder thickness
5. Expand only what the crew actually completes

More detail for plant contexts lives in [preventive maintenance for plants](/guides/preventive-maintenance-for-plants). Skipped PM does not reduce downtime — finished PM can.

When predictive is worth it

Predictive maintenance is worth piloting when all of the following are true:

• The asset is critical enough that a miss hurts capacity or safety
• A signal reliably precedes failure (not just noise)
• Alerts create owned work orders with parts readiness
• You can measure alert-to-complete time and repeat-stop reduction
• Reactive capture and basic PM already work — otherwise alerts become another ignored stream

If work orders are still living in chat, buy execution discipline before sensors. Predictive honesty beats predictive hype.

How a CMMS supports all three

A [CMMS](/guides/what-is-a-cmms) is the system of record for maintenance work, regardless of trigger:

• Reactive — fault → work order → restore → history
• Preventive — schedule → due job → owned completion
• Predictive — signal/alert → work order → action → history

Without that spine, each maintenance “type” becomes a separate spreadsheet or notification inbox. The CMMS does not replace MES or a vibration platform; it is where work becomes owned and durable.

Maturity sequence for mid-sized plants

A practical sequence for most mid-sized manufacturers:

1. Capture reactive work on critical assets with timestamps and notes
2. Stabilize handoffs so shift change does not erase diagnosis
3. Add short PM inside real windows on the noisiest failure modes
4. Review weekly — repeats, overdue PM, long restores ([reduce equipment downtime](/guides/reduce-equipment-downtime))
5. Pilot predictive selectively on one critical asset family with a clear response path

Corivo is built for steps 1–4 as a manufacturing CMMS: work orders and PM with plant-floor ownership and facility-based pricing. Use it as the execution layer before (or beside) any predictive stack — so signals have a place to become completed work.