recycling applications, says its latest Autosort machine delivers advanced accuracy of complex sorting tasks at high throughput rates. A combina- tion of a broad range of sensors and use of data to classify objects, enables it to separate materials that are difficult, or even impossible to separate using conventional technologies, the company claims. It collects up to 320,000 scan points per second to ensure accurate identification of a wide range of materials. Tomra has also developed two flake sensor-based

Above: Tomra’s Autosort

technology in operation

Italy. The line can now treat 20 t/h of mixed plastics from urban collection, to produce more than 22 high quality final products separated by polymer, colour, density and size through a combination of various sorting technologies. This is part of one of the largest material recovery facilities (MRF) in Europe that receives, sorts, separates and prepares recyclable household waste plastics. The upgrade involved installation of various new

Right: Recycled PP flakes

pieces of sorting equipment, including numerous Autosort units from Tomra Sorting Recycling. All told, there are now 32 Autosorts on various lines in the facility (16 were installed in the latest expan- sion). Autosort machines combine NIR (near-infrared wavelengths) and VIS (visible wavelengths) sensors. “Thanks to the highly

accurate sorting carried out by the Autosort units, in addition to recovering single-layer PET trays, the Masotina facility can also target and recover multi- layer PET trays, with the end recovered fraction meeting the quality requirements set by Corepla for use as food-grade rPET,” says Tomra. Corepla is Italy’s national consortium for the collection, recycling and recovery of plastic packaging. Autosort units use air jets to divert different materials into separate streams. Tomra says the latest advances in sensor-based

sorting technology are making it possible to achieve purity results that are far higher than those achieved by any other plastics sorting technique. Sensor-based sorting technology is now capable of sorting coloured and clear types of plastics. Tomra, which was responsible for the develop- ment of the world’s first infrared sensor for waste


sorting solutions, the Autosort Flake and the Innosort Flake, which can achieve “unparalleled” recovery and purity rates of PET, as well as PE and PP. Innosort Flake combines a dual full colour-camera and Tomra’s NIR Flying Beam polyolefin-specific sensor to sort PE and PP by both colour and material; Autosort Flake is designed for high-end applications, such as bottle-to-bottle recycling, where quality demands are particularly high and contamination levels of the infeed material are low. It simultane- ously detects colour, metals and enhanced material information regardless of grain size. Both Innosort Flake and Autosort Flake can be used in combination with Autosort machines to form a full optical sorting line for flake sorting. Tomra Autosort is used to pre-sort the material then Innosort Flake and Autosort Flake are used for flake sorting. Highly integrated pre-sorting and flake sorting solutions pave the way for cleaner end products and recycled PET and PO resins, says Fabrizio Radice, VP, Head of Global Sales and Marketing at Tomra Recycling. “Further- more, if the same supplier is used for both the pre-

sorting and flake sorting machines, higher levels of

accuracy can be achieved as the solutions are built to work in unison.” Also involved in the project at

Masotina was ZenRobotics, which installed an AI-powered robotic sorting station to ensure a high purity rate of clear PET. ZenRobotics’ Fast Picker sorting station performs quality control at the facility, improving efficiency and reducing the need for manual sorting. Plastic waste is first sorted from other recyclable

materials, and then separated by polymer and colour using optical sorters. Juha Mieskonen, Head of Sales at ZenRobotics, says the Fast Picker removes contaminants and takes out other




E :





Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57  |  Page 58  |  Page 59  |  Page 60  |  Page 61  |  Page 62  |  Page 63  |  Page 64  |  Page 65  |  Page 66  |  Page 67  |  Page 68  |  Page 69  |  Page 70  |  Page 71  |  Page 72