MaintenanceVerified Real deployment at a named or precisely described company, with a measured result from a primary source.

Predictive maintenance from vibration sensors, planned in the CMMS

Added 2026-10-12 · Last updated 2026-10-14

Role

Maintenance & reliability · Typical users: maintenance manager

The problem

Rotating equipment (pumps, gearboxes, motors, fans) often fails without obvious warning, and an unplanned stop on an extrusion or process line costs hours of repair plus hours to bring the line back to temperature. Route-based checks miss problems between visits, and maintenance teams end up reacting at night or on weekends. Fiberon estimated one avoided melt-pump failure alone at $56,000 and 16 hours of downtime.

Step by step

1. Rank assets by cost of failure and pick 20–40 critical rotating machines for a pilot.
2. Install sensors and confirm data is flowing; record each asset's type, speed and bearing data so faults can be diagnosed.
3. Define who receives alerts and the response time expected; Fiberon's six-person pilot team included maintenance, planning, plant and engineering managers.
4. Link alerts to the CMMS so each one becomes a work order with the diagnosis, recommended action and urgency.
5. Inspect to confirm before repair, then plan the job into the next shutdown when the risk allows.
6. Record every save (hours and cost avoided) and every false alarm, and review them monthly with the vendor.
7. Scale to more assets once response rates and documented savings justify it.

Tools

• Augury Machine Health: used at Fiberon
• Other condition-monitoring platforms: AssetWatch, Tractian, Waites, Siemens Senseye, SKF
• CMMS to receive work orders: SAP PM, IBM Maximo, Fiix, UpKeep, MaintainX, Limble

As reported by the source; most figures are vendor or self-reported and not independently verified.

Human review: cautions

• Savings are estimated by the plant and vendor (cost avoided), not audited.
• Sensors work best on rotating equipment; electrical faults or process issues need other methods.
• Alerts are only useful if someone acts on them; agree on response times before you start.
• Keep failure codes clean in the CMMS so you can prove what was avoided.

You are a reliability engineer.

Inputs: (1) the condition-monitoring alert: asset, sensor readings and trend, diagnosed fault, (2) the asset's CMMS history for 24 months, (3) the production and shutdown calendar for the next 6 weeks, (4) spare parts on hand.

Tasks:
1. Explain the likely fault and how fast it could progress, citing the readings.
2. Draft a work order: inspection to confirm, repair steps, parts, skills, duration, lockout notes.
3. Recommend when to do it (now, next weekend, next shutdown) with the risk of waiting.
4. Do not calculate cost avoided yourself: list the inputs needed (downtime hours planned vs unplanned, cost per hour, parts and labour) in a small table I can fill in a spreadsheet.
Cite the readings or CMMS lines behind each statement; write 'not found' when data is missing.
Use only the data I paste in; if something is missing, write 'not found' or list it as a question instead of guessing. Do not send, order, post or change anything in any system: produce drafts for my review and approval.

Sources

• https://www.plantservices.com/predictive-maintenance/article/55307059/ai-powered-maintenance-cuts-downtime-and-costs-for-fiberons-manufacturing-operations
• https://www.plantemoran.com/explore-our-thinking/insight/2026/06/ai-use-cases-in-manufacturing