Machine learning for RO increases permeate production by 6.2%, reduces CIP frequency
Cleaning reverse osmosis (RO) membranes is critical to meeting daily production targets and avoiding the high costs of replacing membranes too early. Deciding when to clean a plant currently relies too heavily on guesswork or generic guidelines. Synauta’s patent-pending solution predicts the optimal time to clean.
Today Synauta released a case study for an industrial plant in Australia with Osmoflo, where we:
- Produced 6.2% more permeate
- Had 8.7% less cleans, saving on chemicals
- Almost doubled projected membrane life
- Enhanced operator decision making with clear recommendations on when to flush and when to clean.
For a copy of the full case study contact us.
Read about the trial in today’s Global Water Intelligence Water Desalination Report click here.
See our other case study with Osmoflo about saving energy in SWRO.