Green Machine LLC

- Hyperspectral Robotic Sorting System



Green Machine’s newly developed Green Eye® Robotic Sorter are the most advanced robotic systems on the market. Our robotic sorters meet specs that no other robotic sorter can match. We’re the first company to make it possible to put up to 30 robots in a row, all functioning off a single Green Eye® Hyperspectral Vision System. Each robotic arm can perform a minimum of 100 picks/minute and can be trained to pick four separate commodities at the same time. Our robotic arms can be built side-by-side to cover conveyor belts up to 72” wide.

Industry’s Most Advanced Robotic System At The Lowest Price Point

Because each independent arm runs off the same vision system, we are able to deploy our robotic sorters at a price point not possible by our competitors, while retaining the capability to pick virtually every type of material our Green Eye® Hyperspectral Vision Systems are famous for including—all paper grades, all polymers, C&D products, textiles, e-waste, ASR, organics and much more—all at the cleanest and fastest pick rates.

Green Eye®Automation and Processing Versatility.

Green Machine’s patented Green Eye® Hyperspectral Vision Systems produce the industry’s most versatile and exacting automated sorting platform. Green Eye® Optical Sorters and newly developed Green Eye® Robotic Sorter technologies have revolutionized the recycling industry. Since our first deployment in 2007, Green Machine’s engineers have continued to perfect our patented 3-D artificial intelligence, high-speed, full-spectral collection systems, driving a wide variety of optical and robotic sorting platforms. Both positive, negative and mixed sorts are achieved through simple training methods. Each system can be trained to sort any material without exception, all on one single optical or robotic unit. Single-use sorters are a thing of the past.

Our Green Eye® Product Testing Facility in Hampstead, N.H., is prepared to provide exhaustive testing of your difficult-to-sort products, ensuring success prior to deployment.

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