Fix what's about to break. Not what already did.
Failure-mode models trained on years of operational telemetry — naming the part, the severity, and the time you have to act. Predictive maintenance, wired into the systems your reliability team already runs.
Four maintenance strategies. Wildly different bills.
Most plants run a mix. The question isn't "which one" — it's "which asset belongs on which rung", and how high you can move the critical ones.
Predictive
Failure-mode models combine signals with operational context to flag what's about to break.
A model per asset class, not a black box per plant.
Generic anomaly detection ages badly. Models that know what a frac pump looks like in late-life — and what's different about a CNC spindle — get sharper with every catch.
- Per asset classA frac pump's failure modes are not a CNC's. Models are tuned to the class, not the catalogue.
- Operational contextDuty cycle, load, ambient — fed in alongside vibration and current so the model sees what the machine sees.
- Failure-mode awareNot 'something is wrong' — 'inner-race bearing damage, severity 6.2, escalating'. Tells the engineer what to fix.
- Continuously retrainedOperational feedback loops back into the model. Every confirmed catch — and every false alarm — improves the next call.
Sense · Model · Predict · Dispatch.
Sense
Vibration, current, thermal, acoustic, and process signals captured continuously at the asset.
Model
Failure-mode and remaining-useful-life models per asset class, tuned with operational context.
Predict
Severity scoring, ETA-to-action, and the specific failure mode named — not just an anomaly flag.
Dispatch
Work order auto-created in CMMS with context, spare part, and recommended crew skill.
The prediction is only useful if the right person sees it.
Auto-generated work orders land in the CMMS you already use — with the failure mode, severity, recommended spare, and crew skill attached. No new inbox. No alarm fatigue.
- CMMS connectors: Maximo, SAP PM, Fiix, UpKeep, eMaint
- Spare parts recommendations from your own MRO catalogue
- Crew skill and shift routing baked into the dispatch
- Audit trail from prediction → action → outcome
Unplanned downtime cut by a third — sometimes a half.
A tier-2 automotive supplier paid for the platform on a single avoided spindle failure.
14 days of bearing degradation modelled in time to plan a weekend changeover — instead of a Monday-morning crash that would have stopped six lines. Year-one ROI from that one event covered the rollout twice over.
Strongest as part of the chain.
Move your critical assets up one rung.
A 30-minute working session with a reliability engineer — calibrated to your critical-asset list and the failure modes that have hurt you before.