OMB Individually Reported
Machine Learning for Chemical Savings at Reverse Osmosis Plants [2024 INV#DOI-73 (NEW)]
Low riskExact public inventory row
Description
Water treatment processes are often complex and maintenance activities present tradeoffs between cost and system performance.
Detailed example
A tool to inform plant operations as to best time to clean/perform maintenance rather than a fixed schedule or threshold.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
This project aims to use machine learning to optimize the usage of membrane cleaning chemicals in a water treatment plant using a reverse osmosis process. This would lower the unit cost of water produced.
Controls / human review
ATO: No; PIA: Not published