Keep plants running
without blind spots in your water systems
Aquanomix delivers AI-powered condition monitoring with real-time control to detect corrosion, fouling, scaling, and efficiency loss across plant water systems—so teams can intervene before failures disrupt operations.
SMALL WATER FAILURES
STOP BIG PRODUCTIONS
Process water systems can degrade quietly until they disrupt production. Microbial growth, scaling, or chemistry drift can contaminate batches or foul equipment like reactors, heat exchangers, mixers, sterilizers, and filling lines—forcing rejected product or unexpected shutdowns.
Aquanomix analyzes real-time water quality and system data using machine learning to detect early signs of failure so plant teams can intervene before production is affected.
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Microbial growth or chemistry drift in process water loops can contaminate product streams, forcing batch rejection, sanitation cycles, or temporary line shutdowns.
Aquanomix detects early indicators before production quality is affected.
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Imbalanced water chemistry accelerates corrosion in piping, vessels, and heat exchangers, increasing the risk of leaks, shutdowns, or premature asset replacement.
Aquanomix continuously tracks corrosion indicators to protect equipment reliability.
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Scaling and fouling in heat exchangers and process loops reduce heat transfer efficiency, slowing temperature control and extending production cycles.
Aquanomix detects early fouling conditions before throughput is impacted.
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Unstable water conditions can trigger alarms, controller instability, or chemical overdosing that interrupts automated production processes.
Aquanomix monitors system behavior to maintain stable operating conditions.
Condition-Based Monitoring
to Protect Production Reliability
We deliver condition-based monitoring for process water systems to protect asset health and production reliability. By continuously analyzing real-time water quality and equipment performance data, Aquanomix detects early indicators of fouling, corrosion, microbial growth, and control instability that degrade critical process equipment.
Machine learning models evaluate patterns across:
Chemistry readings
Heat-transfer performance
Controller behavior to identify developing failure conditions
HOW IT WORKS
1 — Collect Real-Time System Data
Sensors continuously capture key water quality and operating metrics—such as pH, conductivity, turbidity, ORP, temperature, and chemical residuals—to create a real-time view of process water system conditions.
2 — Detect Early Failure Signals
Machine learning analyzes patterns in the data to identify early indicators of fouling, corrosion, microbial growth, or control drift.
3 — Diagnose Asset Health
The platform translates these signals into insights about equipment condition and system performance.
4 — Intervene Before Production Is Impacted
Operators receive alerts and recommendations so corrective actions can be taken before reliability or production is affected.
Example 1: heat exchanger fouling
A process heat exchanger begins accumulating scale, gradually reducing heat transfer efficiency. Real-time water quality and temperature data show a subtle change in system performance. Aquanomix detects the early fouling pattern and identifies the developing condition so operators can intervene before production throughput slows or the exchanger requires a shutdown for cleaning.
Example 2: corrosion in process piping
Process water chemistry begins drifting outside optimal conditions, increasing corrosion risk in piping and vessels feeding a production line. Real-time chemistry data reveals the shift before physical damage occurs. Aquanomix detects the developing corrosion indicators and alerts plant teams so conditions can be corrected before leaks, equipment damage, or an unexpected line shutdown occur.
Reactive Maintenance
Problems are addressed only after equipment performance declines or production is disrupted.
• unexpected production shutdowns
• emergency maintenance events
• batch rejection or loss
• equipment damage
Scheduled Maintenance
Water systems are serviced on fixed schedules regardless of actual operating conditions.
• unnecessary maintenance work
• developing issues go undetected
• inefficient chemical usage
• limited visibility between inspections
Condition-Based Monitoring With Aquanomix
Water systems are continuously monitored so early failure signals are detected before performance is affected.
• early detection of fouling and corrosion
• improved equipment reliability
• stable production conditions
• optimized maintenance intervention
Start Monitoring Process Water the Same Way You Monitor Critical Assets
from reactive water management
to condition-based reliability
Most industrial facilities manage process water systems using either reactive maintenance or fixed service schedules. Problems are often discovered only after production performance declines or equipment damage has already begun.
Aquanomix applies condition-based monitoring so plant teams can detect early failure signals and intervene before water conditions degrade asset health, disrupt production, or increase operating costs.