JD Ambati, CEO of robotics company EverestLabs, believes AI-powered robotic sorting can help improve both the efficiency and safety of MRFs. | | Courtesy of EverestLabs
The recycling and waste industry is undeniably affected by labor shortages.by U.S. Census Bureau Labor, the unemployment rate in the waste management and remediation services category, which includes MRF workers, increased from 2.9% to 7.9% in November alone. Coupled with the looming potential recession, it is a race against time for industry leaders to navigate this volatile situation and identify solutions to ensure business continuity.
For MRF, rapid innovation is the answer to success in a downturn.
Life cycle of innovation in the recycling industry
The recycling and waste sector has experienced a fairly robust timeline of innovation, beginning in 1800 with horse-drawn carriages that transported waste to incinerators. ” was introduced in 1936, followed by an automated side-loader garbage truck in 1969.
That said, innovation in the MRF equipment industry stalled after the introduction of optical sorters for plastics in the late 1980s, and was delayed until computer technology brought recycling robots to market in 2015.
AI and robotics have become much more accessible in recent years. Computing power available per dollar increased tenfold As measured in floating-point operations per second (FLOPS) or millions of instructions per second (MIPS), it has run roughly every four years over the last quarter century. This makes complex AI algorithms cheaper to run,
JD Ambati
Faster. At the same time, innovations in software and hardware allow robotic cells to perform critical, unstructured tasks.
As a result, AI and robotics can outperform humans on cost. It is easy for MRF to leverage these systems to reduce reliance on humans and increase material recovery in a labor shortage. MRF is increasingly recognizing the benefits of recovering more material using these techniques.
AI and robotics improve operational efficiency and reduce costs
MRF operations are very complex. According to the Waste Business Journal, in the U.S. today, MRF’s average throughput is about 190 tons per day, nearly double his average daily throughput of his MRF in 2000. latest directory of a recycling facility.
Even with robots, there are still a significant number of materials that must be sorted by human workers. Coupled with long hours of standing and undesirable conditions, the effectiveness and efficiency of even the strongest workers declines over time, resulting in high pollution rates and recyclable resources that simply end up in landfills. and reduce the overall accuracy of recovered recyclable resources.
Implementing AI-powered vision systems can greatly improve the accuracy, speed, and effectiveness of robotic detection and picking of recyclable materials. Such AI software, trained on a dataset of hundreds of millions of real-world recyclable objects, computes items to be picked by robotic cells with inference speeds as fast as 12 meters per second and accuracy greater than 95%. and can be identified. With real-time data analysis, AI solutions can also provide actionable insights to help MRFs optimize their lines and prevent their effectiveness from declining over time.
Additionally, the MRF is a labyrinth of conveyor belts, heavy equipment/machinery, sorting stations, and aisles. Also, safety risks limit the number of belts a human can pick. If the main purpose of the sorter is to pick bottles, containers and aluminum cans one by one, it is much more economical and safer to introduce AI and robotics to reduce human dependence and intervention.
While traditional sorting equipment and robotic systems are large and expensive to deploy, modern robotic cells available on the market today are designed to be cost-effective and have a small footprint, allowing Can be placed virtually anywhere. No equipment modifications are required and the deployment does not cause downtime. As a result, MRF deploys his AI and robotics on weekends or off-duty hours, and in a few days he can start collecting up to 2 to 4 times more high-quality recyclables.
Innovation with AI and Robotics
No two recycling facilities are the same. Therefore, it is important for operators to work with a partner who can best understand their needs and provide the right solution for their facility and operations. This allows facilities to get the highest possible levels of efficiency and effectiveness from AI and robotics.
In short, MRF is the central gatekeeper of the circular economy. Ensuring that MRF innovates ahead of increasing socioeconomic challenges is mission critical as it helps MRF overcome labor challenges and ensure continuity. At the same time, it ensures the recovery of more valuable recyclable resources.
JD Ambati is the founder and CEO of EverestLabs, a rapidly growing Silicon Valley company. EverestLabs is working to decarbonize the packaged goods industry by automating recycling using AI and robotics. With over 20 years of experience, including a master’s degree in computer science and artificial intelligence (AI) and a bachelor’s degree in chemical engineering, his Ambati background transforms the way systems enhance the operational efficiency of businesses. Covers his AI applications.
Views and opinions expressed are those of the author and do not imply endorsement by Resource Recycling, Inc.If you have a topic you would like to cover in your editorial, please provide a short suggestion. [email protected] for consideration.
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