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Revamping MRFs with Recycling Robots Using AI and Computer Vision

As the world’s population continues to grow, so does the amount of waste we produce. Recycling is a crucial process for reducing the negative impact of waste on the environment, but sorting and processing recyclable materials is a labour-intensive and time-consuming task. However, advances in technology are transforming recycling facilities with the introduction of recycling robots that use AI and computer vision to sort waste materials more efficiently and effectively. 

Identifying Recyclates with Computer Vision 

When recyclable material is delivered to material recovery facilities (MRFs), it must be sorted and segmented according to its type. Plastics must be separated from paper so that each recyclate can be bundled and sold on to recycling processers, for example.  

The first step in the sorting process is to identify each recyclate and determine its composition. Traditionally, this task was carried out by individual staff members, who classified the recyclates based on their visual appearance. As you might expect, this takes a considerable amount of time and requires a significant number of staff.  

Fortunately, technological advancements and the use of computer vision now enables MRFs to increase the speed at which identification can be carried out.  

Recycleye Vision highlights the impact that computer vision can have on the sorting process, with the ability to classify recyclates across limitless material classes. As well as detecting the material of each recyclate, computer vision can also differentiate between food-grade and non-food-grade packaging, as well as between colours, shapes, and brands.  

By generating accurate data for transparency and traceability, computer vision also enhances the management of recyclates and ensures MRFs can keep records for compliance at every stage of the sorting process.  

Sorting Recyclates with AI Robots 

Once recyclates have been identified, they need to be sorted according to their type, material, grade, and so on. Again, this is a task often conducted manually, with sorters picking individual recyclates and placing them in relevant containers or bins before balers compact the recyclates prior to shipping.  

With robotic sorting solutions, however, this task can be completed more quickly and accurately. When used in conjunction with Reycleye Vision computer vision, Recycleye Robotics enables MRFs to fully automate the sorting process and streamlines operations accordingly.  

What Are the Benefits of Combining Sorting Robots and Computer Vision? 

As the latest development in solid waste treatment equipment, computer vision and robots for waste sorting deliver a variety of benefits to MRFs, including: 

Enhanced Accuracy 

Accuracy is extremely important on a sorting line as it affects the purity of the output and, therefore, the value of baled recyclates. A low accuracy rate can significantly devalue the output, while the need for manual quality control protocols increases the time and cost of processing recyclates.  

With full automation, however, MRFs can increase the accuracy of the sorting process and avoid unnecessary sorting errors. At one MRF, Recycleye’s AI plastics sorting robot increased purity to 99% and achieved a volume increase of 12%, highlighting the impact artificial intelligence can have on the accuracy of the sorting process.  

Increased Efficiency 

Efficiency has a direct impact on profitability, which is why it’s important for MRFs to enhance their efficiency wherever possible. In the past, optimising efficiency has sometimes come at the cost of reduced accuracy, but computer vision and AI technology means this is no longer the case.  

Using a 6-Axis design for rapid pick and shoot operation, Recycleye Robotics is capable of delivering up to 33,000 picks from co-mingled dry mixed recycling (DMR) in a 10-hour shift. On a paper line at one MRF, this delivered a significant increase in yield by boosting performance to up to 55 picks per minute. 

Improved Workplace Safety 

Workplace safety is a top priority in any industrial environment, including MRFs. When numerous staff members undertake sorting, this can result in a larger number of people working with and around potentially harmful equipment and the potential for accidents. 

With increased automation, MRFs can reduce their need for sorting staff and, therefore, lower the number of personnel working on the sorting line. As a result, MRFs can enhance workplace safety, reduce the risk of injuries, and protect their liability. 

In addition to this, computer vision and AI sorting robots can successfully identify and remove flammable items, such as aerosol canisters from sorting lines. This significantly reduces the risk of fires and, therefore, further enhances the safety of the MRF and its operations. 

Increased Output Value 

Increased efficiency and enhanced accuracy optimise the purity of outputs on a sorting line and, therefore, boost the value of recyclable material. Maximising revenue and increasing cost efficiency is vital at MRFs – if the cost of sorting recyclates outweighs their value, the process becomes redundant. 

By maximising output value via enhanced accuracy and efficiency, computer vision and sorting robots can support the profitability of the recycling industry. In doing so, MRFs can scale their operations, which should lead to a larger amount of waste being recycled. In turn, there are positive environmental benefits, and less waste is discarded in oceans or sent to landfill.  

Cost Savings 

Cost reductions are a primary motivator for MRFs when it comes to installing sorting robotics solutions and computer vision technology. By increasing the speed at which recyclates are identified and sorted, MRFs can process more recyclable material and increase their overall output.  

In addition to this, the enhanced accuracy that can be achieved with a sorting robot and computer vision increases the resale value of recyclates, reduces the need for quality control processes, and enhances operational efficiency even further.  

When you combine the improvements in accuracy with the increased efficiency rates available, it’s easy to see how advanced solutions, such as sorting robots and computer visions, enable MRFs to significantly reduce their operating costs and increase their profitability.  

Integrating Recycling Robots and Computer Vision into MRFs 

The wide range of operational and financial benefits that recycling robots and computer vision offers make it clear that MRFs can benefit from integrating advanced automation solutions into their sites. To learn more about the impact that our solutions can have on your performance, contact the Recycleye team now at [email protected]. 

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