How artificial intelligence helps recycling become more circular
The process of sorting things for reuse gets faster and more specific.
Smart robots, sensors and vision systems fortified with machine learning software are creeping into production at recycling facilities in Colorado, Japan and Europe.
The promise is twofold: Not only could these technologies help speed up the rate at which incoming items can be sorted, they could dramatically improve the accuracy with which operations can identify specific types of plastics and other materials — including one scourge of today’s system, items contaminated with food and other substances.
Two companies talking up the potential to make the act of processing everything from plastic to demolished construction materials far more efficient and scalable include five-year-old startup AMP Robotics, a machine learning and computer vision specialist headquartered in Louisville, Colorado. And a middle-aged Norwegian company, TOMRA, got its start managing reverse vending machines that uses sensors to endow its food sorting and recycling systems with more intelligence.
A new vision for sorting
As its name suggests, AMP Robotics’ innovations lie in how it’s rethinking recycling robots. Founder and CEO Matanya Horowitz began receiving grants back in 2014 to research and develop vision systems that could improve the accuracy of separating items with machines rather than by humans. The company’s equipment is "trained" by being shown millions of images — everything from logos to box shapes to dyed plastics.
"If you can teach a person to distinguish something, you can teach our vision system to distinguish it," said Horowitz, speaking about this topic this week at Circularity 19.
For example, the technology — using a combination of light and machine learning software — could be used to sort out colored whipped cream tubs or yogurt containers from clear plastics. It can even identify items that carry a specific brand logo. One early adopter, Alpine Recyling in Colorado, recently was able to add coffee cups to the mix of stuff that its facility can handle. These levels of specificity could be valuable for consumer products companies seeking either to put their own product packaging back into circulation or to buy specific types of plastics.
"We can track what is truly being recycled," Horowitz added, and that could help provide insight into where better collection systems — and messaging — might be needed.
AMP’s latest technology is a dual-robot system called Cortex, which the 35-person company will sell for municipal solid waste, electronic waste and construction and demolition applications. The equipment can sort, pick and place items at a speed of 160 pieces per minute. More important, it will allow facilities to tackle a process that typically has been very difficult to scale — separating post-consumer fiber from cardboard to sheets of paper.
Horowitz is cagey about how much money his company has raised, although its backers include Closed Loop Partners, and he called out the Alphabet company Sidewalk Labs during our conversation. Likewise, he won’t talk about the cost of his firm’s technology, pointing out that customers are seeing a payback of less than two years and that it sorts at the rate of two people.
AMP Robotics is also touting applications in the construction sector. Earlier this year, it disclosed a partnership with Japanese waste management company Ryohshin to sell AI-driven robots for recovering materials out of demolition debris — including wood, metal, electronics and concrete.
Materials in black
TOMRA, which last week joined the Alliance to End Plastic Waste, is credited as the inventor of near-infrared sensors for sorting applications. It holds close to 80 patents, and has extensive experience with sensors that can provide information about moisture or chlorine levels as items are being washed and sorted. The company’s technology is installed in roughly 100,000 locations worldwide; aside from recycling and collection, the company sells to food operations that need to sort things such as fresh produce.
"We urgently need to transform the recycling industry by creating value out of waste," said Stefan Ranstrand, TOMRA president and CEO, in a statement. "In some markets, recycling rates are as high as 98 percent, and some consumer goods companies are now making new products out of 100 percent recycled materials. But this is only a very small part of the picture, and much more must be done to preserve our world for generations to come."
Two of TOMRA’s most recent innovations include a material recognition sensor that can sort single-layer polyethylene terephthalate (PET) trays (think cafeteria trays) and a new laser feature. The latter development helps TOMRA's systems detect black objects that are typically hard to ID, as well as those with certain shapes, such as silicon cartridges. Over time, the AI associated with these systems will be able to detect the presence of films within rigid plastics, according to the company’s website.
"If you really need to sort out materials to the highest quality possible, you need to be able to do this," said Volker Rehrmann, executive vice president of TOMRA and head of the 4,000-person company’s newly formed circular economy team.
AI has been part of TOMRA's technology for some time — some level of algorithmic detection was introduced as part of its original bottle collection machines. The company collects 40 billion used beverage containers annually through those reverse vending machines. So it has plenty of legacy experience, which will be vitally important for finding value in the wide range of plastics that now exist in the world.
"Without going into the details, it now needs to be much more accurate than it used to be," Rehrmann said.
That’s because even though recycling is big business — an estimated $110 billion in America alone last year — he estimates that only 2 percent of those materials are valued as a resource, not waste, within a closed loop economy. That’s a problem that the Alliance to End Plastic Waste is determined to address. "They have realized that change is necessary," Rehrmann said.