Predictive Cleaning-in-Place (CIP) Scheduling

Membrane fouling in RO systems leads to reduced efficiency, increased energy consumption, and frequent cleaning. Traditionally, CIP procedures are performed on fixed schedules or after performance deterioration. The goal is to predict the optimal cleaning time before serious performance loss occurs.

The SensQuant system applies AI algorithms to monitor real-time trends in key RO parameters such as normalized flow, differential pressure, and salt rejection. Using historical data and machine learning models, it forecasts fouling progression and recommends the ideal time window for cleaning. The system provides alerts and integrates with maintenance planning tools.

This predictive approach reduces unnecessary cleaning, minimizes chemical use, and extends membrane lifespan. Operators receive timely, data-driven recommendations, resulting in lower OPEX, more efficient plant operation, and enhanced membrane performance without guesswork.