ASSET RELIABILITY
Condition Monitoring & Predictive Maintenance
Detect developing equipment problems before they become production failures. CANS combines vibration, temperature and operating context with edge analytics, trending and maintenance workflows for motors, pumps, fans, gearboxes and other rotating assets.
The objective is not to generate more alarms. It is to give maintenance teams earlier, better evidence for deciding what needs attention, how urgently, and why.
From sensor to maintenance decision
PyXis vibration + temperature sensing
↓
Edge signal processing & fault indicators
↓
CruxNEXUS trends, context & analytics
↓
Alarm prioritisation & diagnosis support
↓
Inspection / work order / maintenance action
WHAT THE SYSTEM LOOKS FOR
Mechanical condition in operating context
Vibration should not be interpreted in isolation. CANS can correlate vibration and temperature with speed, load, process state, operating mode and maintenance history so that abnormal behaviour is assessed against the conditions under which the machine is actually running.
Vibration severity
RMS velocity and acceleration trends, axis-by-axis behaviour, rate of change and site-specific alarm thresholds.
Frequency-domain evidence
FFT peaks, harmonics and characteristic patterns associated with imbalance, misalignment, looseness, bearing faults, resonance and related machine conditions.
Thermal & process context
Temperature, run state, loading and process variables help distinguish a real deterioration trend from a normal change in operating condition.
A practical OT architecture
PyXis can be deployed at the machine layer and integrated through industrial communications into existing PLC, SCADA, historian, edge or CruxNEXUS environments.
For brownfield plants, CANS can start with a limited set of critical assets and expand only after the signal quality, alarm logic and maintenance workflow have been validated.
Machine layer — PyXis triaxial vibration + temperature sensing
Connectivity — Modbus RTU / industrial gateway / existing control network as applicable
Operational layer — PLC / SCADA / historian / CruxNEXUS
Analytics — trends, FFT evidence, severity indicators, fault signatures and contextual rules
Maintenance workflow — inspection request, CMMS work order, intervention and post-maintenance verification
WHERE IT FITS
Prioritise assets where failure has consequence
Motors · pumps · fans · blowers · gearboxes · conveyors · compressors · cooling-water equipment · production machinery
The strongest business case is usually not blanket instrumentation. It is targeted monitoring of assets where unplanned failure causes production loss, quality impact, safety exposure, difficult access or expensive secondary damage.
Recommended deployment approach
1. Asset criticality review
Select machines where condition information can change a maintenance decision.
2. Baseline measurement
Establish normal behaviour across realistic loads and operating modes.
3. Alarm and diagnostic tuning
Use plant-specific data rather than generic thresholds alone.
4. Maintenance integration
Define who receives an alert, what evidence is shown, and what action follows.
5. Scale after validation
Expand to additional assets only after the workflow proves useful.
Need a budgetary design?
Send us the equipment list, motor ratings, operating duty, existing PLC/SCADA architecture and the maintenance problem you are trying to solve. We can propose a practical pilot scope and integration architecture.