Using artificial intelligence to improve Energy-from-Waste plant performance
Avoid non-conforming waste to ensure a continuous activity in energy from waste plants
As part of its waste recovery activity, SUEZ has set up an industrial sorting process: waste is sent to a transfer station where it is monitored remotely by operators, via screens, before being sent to a plant where it will be incinerated to produce electricity. This process requires the constant focus of the operators, who must observe up to 8 screens simultaneously to detect non-compliant items in the continuous waste stream. These are typically bulky objects, such as mattresses, metal pipes, supermarket shopping trolleys or rubbish bins.
Using artificial intelligence as an extra set of eyes
The solution was developed in a three-part collaboration between the Group Digital team, SUEZ in the UK, and a startup partner called Deepomatic. A Proof of Concept (POC) was first completed in 2019 as part of the SUEZ Digital HUB Acceleration Program, and the solution was later industrialized and deployed with the support of the Group Data Office in 2020.
AI Project (short version)
Credit: SUEZ UK
Increased detection of non-compliance objects helps plants’ blockages decline
In 4 months of operation, the system detected 11 non-conforming items that were missed by the operator and could have caused blockages. Since deploying the solution, the EfW plant experienced a sharp decline in shutdowns, and the Group is looking to scale up the solution to other EfW sites in the UK, France, and Belgium.
The SUEZ Digital team, in collaboration with R&R UK operational teams, built and deployed a unique artificial intelligence solution that has been integrated into the daily operations of our sites in West London. In just six months of operation, the system has helped operators detect many non-conforming items, and we've seen a significant reduction in plant shutdowns over the period.
John Scanlon , CEO, SUEZ R&R UK