Optimal performance of any membrane system to operate at the points of highest efficiency and lowest cost requires a delicate balance; Cleaning membranes too frequently reduces the system lifespan, too infrequently reduces product quality and increases energy costs. Providing proper maintenance of membranes is not a one-size-fits-all approach, as each system and each train are unique based on their purpose, age and placement within a treatment system.

What if it were possible to detect early warning signs of fouling to minimize the amount of time troubleshooting the system?

Maintaining membrane systems on their unique cycles and fouling rates, rather than a manufacturer’s specified time-frame, allows for maximization of operating conditions and total profits.

The challenge of membrane longevity and integrity is that each system design is unique to it’s plant location and objective. These factors also depend on the feed water source and the target product water quality. Plant managers and service engineers are required to maintain and when possible, reduce, total O&M and energy costs in order to meet achieve product margins.

How can I predict the best cleaning schedule for my membrane systems?

Analysis of the challenges of each specific train can depend on regional water quality, past performance and energy used are complicated equations based on a wide variety of factors. Applying data science to a plant’s existing data streams can provide insights to predict the ideal time to clean and service a membrane to improve and extend performance and life cycles of membrane systems to help manage these costs.

The unexpected shutdown of a membrane system can be a catastrophe for any processing plant. This can be due to the product water quality deteriorating or having to discharge the system to identify a membrane problem.

What if you could have peace-of-mind that each system was being maintained regularly and have remote monitoring to oversee the entire operation?

Remote monitoring centers now have the opportunity to use Big Data and informed decision-making to collaborate with service engineers in the field and add to the value delivered. Pluto’s predictive analytics dashboard provides data analytics and actionable insights to these big companies in order to optimize how they maintain a global fleet of membrane systems 365 days/year.

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