Tomra sees paper and plastics applications for GAINnext

Technology provider says GAINnext can use deep learning to reduce impurities in sorted and recycled paper and plastic grades.

paper grades recycling tomra
Tomra says its GAINnext paper cleaning application “uses deep learning technology to effectively remove impurities like pizza boxes, egg cartons and other brown boards from the paper stream.”
Image courtesy of Tomra Recycling Sorting

The Tomra Recycling Sorting business unit of Norway-based Tomra Systems ASA says it has identified two popular applications at North American material recovery facilities (MRFs) for its deep learning or artificial intelligence (AI)-based GAINnext sorting device.

Tomra says the PET Cleaner and Paper Cleaning applications for GAINnext have been developed based on the machine’s ability to “recognize feed material encountered by recyclers in North America.”

The deep learning technology, says the firm, can help GAINnext “recognize hard-to-classify objects, reducing the need for manual sorting.”

Continues Tomra, “Capable of identifying thousands of objects by material and shape in milliseconds, these new GAINnext applications help recyclers to reduce polyethylene (PET) and paper bale impurities, enabling operations to create new revenue streams, increase profitability and decrease costs.”

“Recyclers can integrate GAINnext into existing lines to boost PET and paper recycling recovery and purity without the need for adding lines,” says Ty Rhoad, Tomra Recycling’s vice president of sales for the Americas.

Continues Rhoad, “This is a significant benefit for operations that are tight on space. These new GAINnext applications process material at up to 2,000 ejections per minute, depending on the application, and can help to reduce the need for manual sorting at the end of the line. This results in up to 33 times more throughput than manual sorting.”

The two new application settings feature technology that “simultaneously integrates multiple sensor data for higher sorting accuracy than traditional optical sorters alone,” states Tomra.

The company says GAINnext can complement its AutoSort sensor-based material identification in a combination it says “maximizes recovery and purity of valuable PET and paper materials at high-throughput speeds.”

By sorting opaque PET, the PET Cleaner application can “remove hard-to-classify PET materials that can lead to downstream sorting and recycling challenges,” says Tomra, adding that the deployment “instantly identifies and removes over 92 percent of opaque objects with titanium dioxide protection.”

Recovered paper producers can use the GAINnext Deinking/Paper Cleaning application for the “high-accuracy sorting” of sorted office paper (SOP), old newspapers (ONP) and old magazines (OMG), says Tomra.

“Capitalizing on multi-sensor integration, the paper cleaning application uses deep learning technology to effectively remove impurities like pizza boxes, egg cartons and other brown boards from the paper stream,” says Tomra.

“Our GAINnext Deinking/Paper Cleaning application can also improve the sorting performance of cardboard-based objects such as frozen food packaging,” says Indrajeed Prasad, a product manager with Tomra Recycling. “By efficiently removing undesired materials like envelopes, wrapping paper and brown paper grocery bags, the system creates high-quality paper revenue streams.”

Tomra Recycling Sorting describes itself as a designer and manufacturer of sensor-based sorting technologies for the global recycling and waste management industry.