As the global population swells, the pressure on our planet’s resources becomes more evident. Recycling is one important way we can all do our part to reduce our environmental impact, and with growing demand for recycled materials, labour availability for sorting and processing recyclables is becoming a key factor in recycling capacity. Fortunately, waste sorting robots provide part of the solution.
By using artificial intelligence to detect what is recyclable, these intelligent machines can take over some of the burden from human workers. This helps not only mitigate labour shortages in this sector, but also improves efficiency and accuracy in recycling operations. So, if you’re looking for ways to make your waste sorting process more efficient, read on to learn more about the potential of waste sorting robots.
Materials Recovery Facilities (MRFs) typically process a wide range of materials, most of which are mixed together (co-mingled). Before materials can be recycled, they need to be separated and sorted into distinct groups. Cardboard needs to be separated from glass jars, cans need to be processed separately to plastic bottles, and so on. Furthermore, non-recyclable and potentially hazardous items need to be removed so that materials can be processed effectively and safely.
Traditionally, these tasks have been carried out by human pickers, but this has some disadvantages. Humans make errors, which can have serious commercial or safety consequences if materials are incorrectly sorted or hazardous materials are not removed, and manual pickers can only sort a maximum number of materials in a set amount of time. In addition to this, labour shortages have resulted in MRFs being understaffed, which limits the number of items that can be processed.
Instead of relying on manual pickers to process and sort materials, robotic sorting solutions are used to automate these tasks. Using AI computer vision, Recycleye Vision scans the co-mingled waste materials before Recycleye Robotics picks and places materials in designated locations. Effectively replacing or supplementing the work of human pickers, robotics sorting solutions operate with high efficiency and accuracy rates, thus minimising errors and maximising productivity.
When waste materials are co-mingled, it can be difficult to identify the specific type of material class to which they belong. Computer vision driven by Artificial intelligence (AI) is able to do this as effectively as the human eye, which is particularly useful in an MRF. With unique algorithms designed to incorporate the wide range of potential recyclable materials present in the MRF, AI technology is used to detect recyclable waste with accuracy equal to a manual picker.
Many people are surprised to learn just how advanced waste robotics and AI computer vision are. Recycleye Vision is capable of recognising materials across 28 different classes and can even differentiate between colours, shapes, packaging and non-packaging materials and food and non-food grades. These capabilities ensure maximum applicability within MRFs and increased quality outputs on processing lines.
Absolutely. At Recycleye, we firmly believe that technology can revolutionise the waste management industry, increase the value of recycling and reduce the negative environmental impact that waste continues to have. The ongoing use of landfills is contributing to climate change and environmental damage due to the release of toxins, greenhouse gases (GHGs) and leachate, yet a considerable proportion of waste sent to landfills doesn’t need to be there.
As waste sorting robots can increase the speed at which materials are sorted for recycling and the accuracy with which items are picked, these innovations can increase the value of recycling and reduce the volume of materials sent to landfill. This will have a positive impact on the environment.
There are many benefits associated with using advanced technology in the waste management industry. In particular, waste sorting robotics can offer:
Recruitment, retention and other staff costs are often a company’s biggest challenge and account for a significant proportion of the organisation’s operation expenses (OPEX). By using an AI-driven waste picking robot alongside human workers, MRFs can manage their OPEX and increase profitability instead.
Typically, technology can operate at a consistently faster rate than humans and this applies to waste robotics too. Capable of delivering 33,000 picks from co-mingled waste in 10 hours, Recycleye Robotics shows just how much recycling automation can increase efficiency and maximise outputs.
Technology can improve quality control (QC) accuracy at reduced cost compared to manual QC. When materials are identified, picked and sorted by AI-driven computer vision, waste sorting robotics increases accuracy and traceability of materials for recycling. This delivers greater purity of outputs, with higher resale value for offtakers.
Today, effective waste management requires complete transparency and traceability, which means implementing processes that enable you to monitor and track how and where materials are processed. With Recycleye Vision items are classified over 100 times to ensure accuracy, while data is provided in real-time to maximise traceability at every stage.
When you’re relying on human workers, there are always variabilities that need to be considered, particularly when labour shortages are making it difficult to find permanent staff. If you have on-site robotic picking and sorting solutions, you can be confident that you’ll always have the resources you need to work at optimal efficiency rates.
Whether you’re launching a new facility or looking for tech that can be retrofitted onto existing equipment, Recycleye Vision and Recycleye Robotics can provide the enhanced waste processing you need to enhance your business performance.
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