Industries · Furnace Monitoring & Heat Treatment
MachineWise for Furnace Monitoring & Heat Treatment.
Live OEE, condition-based monitoring and predictive maintenance — engineered for heat-treatment shops. Software-first deployment, rupee-denominated results.
Sealed quench furnacesPit & bogie hearthInduction heatingTempering & annealingContinuous lines
What this floor loses today
The losses every heat-treatment shops knows — and nobody measures.
IDLE ENERGY
Heating nothing
A furnace at temperature with no batch inside is your most expensive idle machine. Idle-energy ratio, measured continuously and priced in rupees.
BATCH TRUTH
Runtime nobody logs
Batch start, soak, quench and unload — timestamped automatically instead of scribbled on a route card two hours later.
PROFILE DRIFT
Silent quality risk
Zone temperature drift that stays inside alarms but outside spec builds rejection batches. We watch the profile, not just the setpoint.
Purpose-built, not repackaged
OEE · CBM · Predictive Maintenance — dedicated to furnace monitoring & heat treatment.
The same MachineWise platform, tuned to the machines, cycles and failure modes of this industry.
LIVE OEE
OEE for this floor
- Batch runtime and utilisation per furnace
- Energy per batch and per tonne
- Loading efficiency — planned vs actual charge
- Door-open events and recovery time
CONDITION-BASED MONITORING
CBM for these machines
- Zone-wise temperature profile monitoring
- Thermocouple health and drift detection
- Burner/element performance trends
- Insulation degradation from recovery-time creep
PREDICTIVE MAINTENANCE
PdM for these failure modes
- Element and burner failure prediction
- Refractory wear indicators from thermal signatures
- Blower and fan health from vibration & current
- Maintenance windows scheduled between batches, not during
15–30%Idle-energy reduction typically identified
₹/tonneEnergy cost per tonne, per furnace
Zone-wiseFull thermal profile, continuously logged
Furnace monitoring system · AI & ML
Condition-based monitoring, tuned to thermal equipment.
A furnace fails differently from a spindle. Its degradation is thermal and slow — recovery times creeping up, zones drifting apart, elements ageing unevenly — which makes it ideal for machine learning and almost invisible to inspection.
THERMAL SIGNATURES
Recovery time as a health index
How long a furnace takes to return to setpoint after a door opening is one of the earliest indicators of insulation loss and element ageing. We trend it per furnace and flag the slope, long before a batch is affected.
ZONE DIVERGENCE
Drift that stays inside alarms
Two zones slowly parting company while both remain within limits is how rejection batches are made. ML compares zone behaviour against the furnace's own learned profile rather than against a fixed band.
ROTATING AUXILIARIES
Fans, blowers and quench pumps
Most furnace stoppages are not the furnace — they are the circulation fan or the quench pump. Vibration and current signatures give the same 48–96 hour warning we give a machine tool spindle.
Keep exploring
Goes deeper with the rest of the platform.
Ready when you are
Run a free 2-machine pilot on your heat-treatment shops — live this week.
Two machines, thirty days, zero cost to start. Live OEE, downtime truth and a plant-specific ROI model — your data on-premises throughout.
Book my free pilot → WhatsApp us