Maintenance / CMMS · 42 features
Predictive maintenance that prevents the problem.
Forty-two Maintenance and CMMS features - work orders, asset management, preventive and predictive maintenance, spare parts, downtime, and reliability - wired to a Predictive Failure Engine that reads vibration, thermal, oil, and ultrasonic streams and warns you 48 to 72 hours before a bearing lets go.
The challenge
- !Equipment fails without warning, and the first sign of trouble is a stopped line
- !Preventive maintenance runs on the calendar instead of on the actual condition of the asset
- !Downtime hours and their true cost are never tracked back to the assets and causes that drive them
- !Sensor data, work orders, spare parts, and reliability metrics all live in separate tools that don't talk
What it does
- ✓Predictive Failure Engine fuses vibration, thermal, oil particulate, and ultrasonic streams, scores anomalies with confidence, and auto-generates work orders before the asset fails
- ✓Full work order lifecycle: request, approve, plan, schedule, execute, and close, with labor, parts, and downtime captured against each asset
- ✓Asset registration with criticality assessment, status tracking, complete service history, and parent/child hierarchy
- ✓Preventive maintenance on time, meter, or condition triggers, with automatic work order generation when a threshold is reached
- ✓Downtime tracking that categorizes planned versus unplanned, documents cause, rolls up cost, and finds repeat offenders with AI pattern recognition
- ✓Root cause failure analysis (RCFA) with investigation, corrective and preventive action, and prevention planning, plus MTBF and MTTR trending and reliability scoring
Inside the module
Every capability, included.
The intelligence
From sensor stream to work order, automatically.
Predictive Failure Engine
Reads vibration, thermal, oil particulate, and ultrasonic streams on every monitored asset, scores anomalies with a confidence level, and opens a work order when a failure is converging - typically 48 to 72 hours ahead on bearings.
Downtime pattern recognition
Categorizes every downtime event, attaches cause and cost, and surfaces the small set of issues driving most of the loss - so the top few failure modes that account for the bulk of downtime are obvious.
Reliability prediction
Trends MTBF and MTTR per asset and class, predicts the next likely failure, and assigns a reliability score that feeds criticality and PM cadence decisions.
Nine workflows
Every maintenance motion, in one place.
The 42 features are organized into nine operational workflows that cover the full lifecycle of an asset - from the day it's registered to the next planned turnaround.
Work orders & assets
Request-to-close work orders against a full asset register with criticality, status, history, and hierarchy.
Preventive & predictive
Time, meter, and condition-based PM alongside sensor-driven PdM with AI anomaly detection and auto work order generation.
Parts, downtime & reliability
Spare parts with reorder alerts, downtime cost tracking, RCFA, MTBF/MTTR trending, and shutdown and turnaround management.
Connected across the platform
One source of truth.
Safety / EHS
Overdue preventive maintenance and degrading asset health feed the Safety Convergence Engine as risk factors, so a neglected machine raises its own danger score before anyone gets hurt.
Quality / QMS
When defects spike, Quality's Root Cause Analysis checks the maintenance status of the asset that made the part, so a worn machine is caught as the source instead of the operator.
Production
Asset availability feeds OEE, and a predictive failure alert can trigger a schedule adjustment so the line is rerouted before the breakdown lands mid-run.
Standards & compliance
Built in, not bolted on.
FAQ
Questions, answered.
How does the Predictive Failure Engine know a machine is about to fail?
It continuously ingests four sensor streams - vibration, thermal, oil particulate, and ultrasonic - for each monitored asset and runs AI anomaly detection across them. When the combined signal indicates a failure is converging, it scores the prediction with a confidence level and automatically opens a work order. On rotating equipment like bearings, that warning typically arrives 48 to 72 hours before the failure, which is enough lead time to schedule the repair into planned downtime instead of reacting to a breakdown.
Can Cortrova run preventive maintenance on condition instead of just the calendar?
Yes. Preventive maintenance supports time-based, meter-based, and condition-based triggers. Condition-based PM uses live asset data and sensor thresholds rather than a fixed date, so a machine that is running clean isn't torn down unnecessarily and a machine that is degrading gets attention early. When any trigger is met, a work order is generated automatically.
How does Cortrova track downtime and its cost?
Every downtime event is categorized as planned or unplanned, tagged with a documented cause, and rolled up to a cost. AI pattern recognition then groups recurring events so the handful of failure modes driving most of your downtime hours and dollars become visible - and those costs roll up by cost center into Finance and inform CapEx decisions based on real failure trends.
How does Maintenance connect to the rest of the platform?
It shares one data model with Safety, Quality, Production, and Finance. Overdue PMs raise risk in the Safety Convergence Engine, a quality defect spike triggers a root cause check against the asset's maintenance status, asset availability feeds Production's OEE and scheduling, and maintenance costs roll up by cost center in Finance.
Does the platform handle major shutdowns and turnarounds?
Yes. The shutdown management workflow covers planning, work packages, contractor coordination, turnaround management, and scheduling, with lockout/tagout handled through the Safety module so the energy-isolation steps are captured as evidence during the outage.
Get started
See Maintenance / CMMS on your shop floor.
We'll tailor a demo to your operation and constraints.