ERI's SAM robotic sorter
SAM is part of ERI’s scrap metal sorting line and separates shredded material, such as aluminum, PCBs, yellow brass, capacitors and copper products, into individual material streams.
Photo courtesy of ERI

ERI improves recovery with robotics

Electronics recycler ERI, headquartered in Fresno, California, is leveraging technology to improve e-scrap processing.

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March 19, 2021

In the first half of 2019, electronics recycling company ERI, which is headquartered in Fresno, California, with locations throughout the U.S., installed an artificial intelligence- (AI-) driven Super Automated Machine (SAM) sorting robot at its Fresno plant. Closely on the heels of that installation, the company added the technology to its Plainfield, Indiana, plant. Within two years, ERI Executive Chairman John Shegerian says SAM will be deployed throughout the company’s six other locations.

“The technology revolution is what created the e-waste problem,” he says. “Now we can leverage technology to address it.”

Meet the robots

SAM is part of ERI’s scrap metal sorting line and separates shredded material, such as aluminum, printed circuit boards (PCBs), yellow brass, capacitors and copper products, into individual material streams. A vision system identifies the target material, directing a robotic arm that uses a vacuum system to pick the desired material. According to ERI, SAM performs approximately 70 picks per minute and can process 10 different streams of shredded material.

ERNIE
Photo courtesy of ERI
ERNIE processes flat-screen monitors and televisions in an enclosed environment.

But SAM is not alone. That system is joined by ERNIE (Electronic Recyclers Next Innovative Efficiency), a robotic flat panel display processor. This proprietary technology can shred 5,000 pounds of flat-screen TVs and monitors per hour in a controlled environment that features a carbon fume scrubber, according to the company.

“No one we know of has a real self-contained flat-screen processing system [like ERNIE],” Shegerian says.

The shredded material produced by ERNIE is routed to ERI’s metal sorting line for commodity-level recovery aided by SAM.

ERI developed ERNIE and SAM in partnership with Amp Robotics of Denver. The process took more than a year, Shegerian says.

Following SAM’s implementation, “It took us about six weeks of machine learning to reach 95 percent efficiency,” he says. By week 10, it had increased to 98 percent efficiency. ERI was able to transfer those gains to its Indiana facility when the technology was installed there.

“This is like our McDonald’s University here in Fresno,” Shegerian says. “This is where we started the company. This is where we built the world’s largest electronic waste shredding machine. We tinker and we evolve all our technologies here first, and then we take them into Indiana second, then Boston and then across America. Everything starts here until we perfect it, and then we take it out from there,” he explains.

The benefits of automation

When electronics arrive at ERI’s facilities, they undergo triage to separate items that are suitable for reuse from those destined for recycling. Contractual issues also factor into this decision. “Some clients want everything destroyed,” Shegerian says. People are integral to this process.

After a trip through the shredder, which produces a particle size of approximately 2 inches, the material encounters an eddy current separator and then SAM.

The combination of ERI’s shredding technology with SAM’s AI and robotics has allowed ERI to produce “cleaner and more liberated commodities,” he says, with “faster production times.”

Shegerian says SAM “picks faster than we can with manual labor,” adding that the technology is 25 percent faster by comparison. SAM also creates a cleaner picking line for ERI’s manual sorters. “It’s going after the lower value stuff so our employees can go after the higher value material.”

He says ERI has seen its overall quality of its recovered nonferrous materials and PCBs increase since implementing the technology. The company also has been able to track its volumes and the composition of the material stream. “It’s constantly being fine-tuned, and the machine learning constantly goes on.”

ERNIE allows ERI to remove its employees from a potentially dangerous environment and makes the processing flat-screen monitors environmentally cleaner. The company went from 10 employees on its flat-screen processing line to three. ERI reassigned those displaced employees to other tasks, including data wiping, parts harvesting and testing and repair, Shegerian says.

Eye on improvement

The AI the system employs provides ERI with constant data on the performance of its shredders, as well as the robotic sorters, helping the company make adjustments to improve efficiency. Anthony Borges, who is vice president of operations for ERI, monitors the data from the system, noting changes in production so they can be addressed. “We’re constantly tweaking for the better,” Shegerian says.

Additionally, he says, “As Amp gets better at what they do, we’ll get better we do. We’re always perfecting our stuff in-house. And, also, we’re looking for our partners to perfect their technology and drive it to be better.”

To keep the technology performing optimally, daily and weekly inspections and servicing are necessary, he says. The ERI team monitors SAM for air line leaks, inspects the robots’ suction cups, checks the air pressure and cleans the filter on the control panel’s air conditioning unit daily. “A lot of maintenance is needed to make sure that it’s a high-functioning part of our company.”

ERI is operating two shifts, Shegerian says, with maintenance performed prior to the start of each shift.

“The technological revolution is what created the e-waste tsunami, and now we could leverage cutting-edge technologies, such as AI and robotics, to help us fix the problem,” he says. “When you get to leverage robotics and AI, people start taking notice. Leveraging technology to take care of the fastest growing solid waste stream in the world, people like that. People like the circularity of that.”