Amp Robotics Corp., a Denver-based company that develops artificial intelligence (AI), robotics and infrastructure for the recycling and waste industries, has announced the launch of two new high-diversion production facilities based on its infrastructure model for advanced secondary sortation.
The facilities are located in Lithonia, Georgia, outside of Atlanta, and in Solon, Ohio, outside of Cleveland, Amp founder and CEO Matanya Horowitz tells Recycling Today. The sites are designed to economically process and aggregate low volumes of difficult-to-recycle mixed plastics, paper and metals sourced from residue supplied by material recovery facilities (MRFs) and other sources.
He adds that the secondary sorting facilities, which are equipped with Amp's robotics and vision systems, allow MRF operators to monetize changing material streams without changing their plants. Amp plans to work with older MRFs that are not designed to capture certain materials, such as polypropylene. "We are still feeling out the landscape," Horowitz says when asked how many tons per month the sites in the Atlanta and Cleveland areas expect to process.
Amp plans to locate additional secondary sorting facilities on the East and West coasts in the second half of the year, targeting major metro areas that have a large number of MRFs, he says.
All of the sites' technology is built around Amp's artificial intelligence that will enable the robots to capture various materials in response to end-market demands. Horowitz says the facilities can create custom material blends for chemical recyclers as well as bales of plastics that are specialized by color or form factor.
“With the success of the pilot facility we launched last year in Denver, we’ve been working hard to bring online additional facilities powered by our application of AI for material identification and advanced automation,” Matanya Horowitz says in a news release about the sites. “This secondary sortation model is helping to address the millions of tons of recyclables and billions of dollars worth of material feedstock lost to landfill despite the demand for high-quality recycled content from consumer packaged goods companies and brand owners.”
Through its secondary sortation model, Amp recovers mixed paper, metals and a portfolio of Nos. 1-7 plastics with a special focus on plastic blends uniquely enabled by AI. The company says its AI platform, Amp Neuron, recognizes 50 billion objects annually, adding that it continues to innovate its AI capabilities to identify and recover film and flexible packaging that can create operational challenges for MRFs, are complicated to recover and expensive to reprocess.
Amp says it’s seeking relationships with waste management companies to accept or buy residual or secondary materials as well as strategic partnerships with plastics reclaimers, chemical recyclers and other plastics manufacturers for off-take of recovered plastics.
Horowitz says the sites will charge a tipping fee, though Amp could be willing to pay for the material depending on its composition.
The launch of the secondary sorting facilities also comes amid Amp’s ongoing expansion of its AI-enables robotics system business, with approximately 230 deployments of its Amp Cortex robotic sorting systems in nearly 80 facilities across three continents, and has doubled its year-over-year revenue for three straight years.
“Data is at the heart of what we do,” says Amanda Marrs, senior director of product at Amp. “Our AI platform, Amp Neuron, continues to achieve breakthroughs in data accuracy and classification of different polymers, form factors and other packaging types. Our neural network is built on a data engine that has recognized more than 50 billion containers and packaging types in real-world conditions."
Marrs adds, “These advancements in material recognition continuously improve performance for our customers and open the door to other categories of packaging that have been historically challenging to identify, such as plastic films and flexible packaging—an area we’re heavily focused on in new product development.”
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