Early fault detection with probable cause
Models compare live vibration spectra, temperature and current against each machine’s learned baseline. Drift is ranked by severity and matched to faults such as bearing wear, imbalance or misalignment.
Predictive Maintenance
Equipment fails between inspections, and the warning was already in the data.
Condition and usage monitoring that moves maintenance off the calendar and onto the signal, turning a failure into a scheduled job.
- Built for
- Maintenance, reliability and plant managers
- Connects
- Retrofit sensors, PLCs and SCADA
- Deploys
- Sovereign cloud, private cloud or on-site
/ The shift /
What happens today, and what changes.
Flip between the operation as it runs now and the operation once the data is joined up.
- 01Maintenance is scheduled by date, spending money on healthy equipment and missing the machine that will not last until its next service.
- 02Vibration climbed for three weeks and temperature drifted.
Nobody was watching that signal on that machine.
- 03Downtime cost is estimated, because no stoppage is attributed to a cause.
/ How it works /
From signal to decision in four moves.
Each step runs on the shared IoT Cube foundation, so nothing here is a separate system to maintain.
- 1
Instrument the critical machines
Retrofit vibration, temperature and current sensors go on the critical assets, and existing PLC and SCADA tags are read alongside.
- 2
Learn each machine’s normal
Signals are linked to the asset, its duty and its operating state, and a baseline is built per machine.
- 3
Detect and rank the drift
Models and thresholds spot deviation from baseline, estimate severity and name a probable cause such as bearing wear or misalignment.
- 4
Plan the job
A work order opens in your CMMS with the evidence attached, and parts and downtime are planned in advance.
/ What you get /
What predictive maintenance gives you.
Condition monitoring across mixed equipment
Machines, gensets, pumps and mobile plant share one asset hierarchy. Sensor data and PLC tags are stored per asset, with operating state used to suppress false alarms.
Signal analysis at the edge
High-frequency vibration and acoustic data are processed on an edge gateway into features such as RMS and spectral bands, so little crosses the network.
Work orders raised automatically
When a fault crosses a severity level, a work order opens in your CMMS or EAM with the asset, trend, severity and recommended check.
Spare parts planned on condition
Detected faults and their expected progression reach procurement, so parts are ordered for the machines that need them.
Downtime and reliability reporting
Downtime events, causes, MTBF and early-detected faults are recorded per asset for reliability reviews.
/ Use cases /
Where teams put it to work first.
Catch bearing wear early
Detect a rising vibration signature on a pump or motor and schedule the repair for the next planned stop.
Protect standby power
Watch coolant, load and run hours on remote gensets, and dispatch before the site loses backup.
Keep vehicles in service
Turn fault codes and engine data from trucks and mobile plant into planned workshop jobs.
Order parts on condition
Share detected faults with procurement, so spares are on hand when work begins.
/ Benefits by team /
Every team gets a different answer from the same record.
01
Maintenance
Technicians spend time on machines that are drifting, and work orders arrive with the fault already described.
02
Operations
Stoppages move from surprise to schedule, and production plans hold.
03
Finance
Downtime and cost avoidance are recorded per asset, giving both budgets a defensible basis.
04
IT
PLC and SCADA data is read through an edge gateway outside the control loop, read-only by default.
/ In practice /
Three moments from a working week.
Each one starts with a signal and ends with someone acting on it. The scenarios are illustrative.
The signal
Vibration on a transfer pump at a Yanbu process plant has been climbing steadily for twelve days.
- 1
The model flags a bearing-wear signature and ranks it as medium severity.
- 2
A work order opens in the CMMS with the trend and recommended inspection.
- 3
Reliability schedules the bearing change for the next planned stop.
The outcome
The repair happens on the plant’s schedule, not the pump’s.
/ Technology /
Four layers. One record underneath.
Device-neutral at the bottom, open at the top, and sovereign all the way through.
01
Devices in the field
Keep the hardware you already have
- Vibration and temperature sensors
- Current and power monitors
- PLC and SCADA interfaces (OPC UA, Modbus)
- Retrofit condition kits
02
Connectivity & protocols
Any carrier, any protocol
- OPC UA
- Modbus TCP / RTU
- MQTT
- LoRaWAN
- CAN / J1939
- 4G/5G via any Saudi carrier
- Ethernet and Wi-Fi on site
03
IoT Cube platform
Sovereign, multi-tenant, AI-neutral
- Time-series store
- AI model runtime
- Edge buffering
- Asset & identity record
- Workflow automation
- Open APIs & webhooks
04
Your systems of record
Data lands where decisions are made
- CMMS and EAM
- ERP
- Spare parts and procurement
- Production systems
/ What you measure /
The numbers this produces.
Measured continuously, per asset, per site and per contract.
Unplanned downtime
Hours of stoppage not scheduled in advance, per asset, line and site.
Faults detected early
Faults found from condition signals before they caused a stoppage.
Planned versus reactive work
Share of work orders raised from schedule or condition rather than breakdown.
Mean time between failures
Average operating time between failures, per asset or asset class.
Alert-to-work-order time
Time from a condition alert to a work order being raised and assigned.
Parts on hand at repair
Share of condition-based jobs where the required parts were ready when work began.
/ Rollout /
Start with one decision. Scale what works.
- Phase 1
Choose the critical assets
We review failure history and criticality with your reliability team, and pick the machines where early warning changes the outcome.
- Phase 2
Instrument a pilot line
Retrofit sensors and PLC connections go onto the pilot assets. Baselines build while threshold alerts run from day one.
- Phase 3
Prove the early warning
Detected faults are inspected and confirmed with technicians, and work orders flow into the CMMS without manual re-entry.
- Phase 4
Scale across the plant
More asset classes, sites and models join the same hierarchy and workflow, line by line.
/ Security & sovereignty /
Where your data lives, and who can reach it.
- In-Kingdom residency
- Built to national controls
- Isolated by tenant
- Your cloud or site
/ Built on IoT Cube /
Products already doing this.
Each one runs this solution on the shared foundation.
Built on IoT Cube
TEFCO
Saudi distributor of IoT and telematics hardware: trackers, dashcams, sensors, RFID, routers and EV chargers, fitted and supported.
Built on IoT Cube
Gorex
On-demand car care and vehicle maintenance, booked in a few taps at a chosen time and place.
Built on IoT Cube
Shipr
Transport management for Saudi road freight: dispatch, driver evidence, delay attribution and bilingual ZATCA invoicing.
/ Industries /
Where this solution shows up.
Industry
Manufacturing & Industry
Machines, utilities and mobile plant reporting condition before they stop.
Industry
Oil, Gas & Energy
Remote assets and contractor movements on one sovereign layer.
Industry
Utilities & Public Infrastructure
Water, power and gas networks that place their own losses.
Industry
Healthcare & Pharma
Cold chain evidence produced as a by-product of the operation.
/ Questions /
Frequently asked.
Most do not. Retrofit vibration, temperature and current sensors clamp on without touching the machine’s controls, and that is where we start.
/ Explore more /
Other solutions on the same foundation.
See predictive maintenance on your own assets.
Bring the hardware you already run. We will connect a sample of it and show you the operating picture it produces.