VIDEO: Digitalising membranes in Oman with Amazon Web Services
The onset of the worldwide Covid-19 pandemic wasn’t the best timing for a new partnership – it meant the collaboration had to be carried out remotely.
The concept needed to harness existing data, combined with artificial intelligence (AI).
"The mission of the co-developing team is to support customers at an early stage of the project, with hands-on implementation using AWS services," said Stephane Paccaud, EMEA Prototyping Engagement manager from AWS.
饮用水希望克莱尔Ventresque补充道:“它was challenging not to be together in the same room. But the result of the project is a testament to the dedication of the team.”
Using machine learning
To start, three years of data from the SUR desalination plant was pre-processed and fed into the Amazon DeepAR algorithm, using its SageMaker service.
This was to learn from previous patterns and predict the future evolution of fouling indicators, such as differential pressure or the conductivity of the water, which enabled the team to anticipate maintenance “weeks or days in advance”.
Over 97 per cent of the mechanical energy is recovered and up to 40 per cent more energy saved than a conventional reverse osmosis plant, according to Veolia.
According to Aditya Akella, operations manager for Veolia Middle East, the ability to plan short-term preventative maintenance now means that the plant can optimise water storage capacity and minimise the "negative impact of an unavoidable shutdown".
Veolia Water France先前已与AWS及其公共云合作，允许它设置虚拟数据中心并在没有任何限制的情况下操作其系统。
“The idea to harness data and AI has been a game-changer,” said Aude Giard, chief digital officer at Veolia Water Technologies. “We have created a substantial edge in the value we can deliver to our customers, particularly improving the operational resilience of water plants.”
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