Recycling food and drink cartons poses certain challenges which need addressing for these materials to form part of a true circular economy. Thankfully, through the use of the latest ground-breaking technology available for sorting systems, progress is being made.
Computer vision now allows carton recycling to be sorted in material recovery facilities (MRFs), a process which has not previously been possible due to cartons being multi-layer – as well as often being mixed up with paper, making it contaminated. In this article, we address the demanding nature of carton recycling and outline how AI waste sorting robots are helping improve recycling to create circularity of materials.
How Challenging Is Carton Recycling?
Although carton recycling can pose some challenges, the good news is that the materials used to make food and drink cartons are highly recyclable, but their multi-layer construction means cartons need to be correctly sorted before they can be sent for specialist reprocessing. Using AI to accurately identify and sort cartons gives rise to the opportunity to increase their recycling rate. Not only is this change beneficial for the environment, but it’s also advantageous for MRFs, the wider waste and materials management industry, and companies purchasing recycled materials.
For effective recycling, cartons must be carefully identified and separated. As cartons tend to be made from a wide variety of materials, this is the most prominent challenge facing MRFs. Food and drink cartons in particular are made from a variety of materials, including aluminium and fibre-based products that are difficult to distinguish with the naked eye. This makes manual sorting time-consuming and error prone, which subsequently affects the quality of the offtake.
Fortunately, artificial intelligence (AI) and computer vision technology is revolutionising the process and making it more efficient to accurately sort and recycle all types of cartons.
Identifying Cartons with AI
When co-mingled waste arrives at a MRF, it needs to be sorted so that different materials can be separated. Traditionally, this was done manually, but new technologies are optimising performance by automating the sorting process.
Recycleye Vision is a great example of how AI is being used to identify cartons at the first stage of the recycling journey. Using computer vision technology, co-mingled waste is scanned, and each item is identified. Capable of classifying materials across unlimited classes, Recycleye Vision can accurately distinguish between different types of carton waste prior to sorting.
Sorting Cartons with AI Robots
Once identified by computer vision, recyclates are deposited in the appropriate location – such as a designated sorting bin. However, MRFs may want to separate recyclates based on more than just the material they are made from. This is possible with Recycleye Robotics, enabling MRFs to classify and sort co-mingled recyclates by material, function and even brand.
The result? A fast and accurate recycling line that utilises AI and robotics to optimise performance and maximise sorting efficiency.
Removing Contaminants from Fibre Lines
When offtake from a recycling line contains contaminants, it decreases the purity, in turn negatively impacting its value. It is vital, therefore, that MRFs successfully remove contaminants from offtake via accurate and efficient sorting processes.
In fibre lines it can be challenging to minimise contaminants due to the nature of the recyclates. When food and drink cartons look similar, manual sorting and processing means materials can be accidentally mixed up. The presence of other materials – such as metals or plastics – in a co-mingled MRF means fibre lines risk being contaminated by these materials too.
Recycleye Robotics: In Action
Deploying a Recycleye sorting robot can be a highly effective way to increase the purity of fibre lines, as highlighted in our recent use study. Here, a client wanted to understand how AI could be used to improve the purity of a fibre line and prevent contaminants from devaluing the offtake.
To facilitate this, we utilised our AI-powered recycling robot to extract cartons and plastics as separate classes, as well as other residual waste and aluminium.
In this example, Recycleye Robotics increased purity by 12% and contaminants were reduced from 15% to just 3%, which highlights the impact AI-powered technology can have on fibre lines and in MRFs in general.
Monitoring Quality and Output
In any MRF it’s essential that quality controls are put in place and accurately monitored. Not only does this allow offtake to be accurately recorded, but it also enables MRF managers to consistently improve processes to achieve higher yields and larger outputs.
Whether it’s carton recycling, plastics recycling, paper recycling or any other type of co-mingled waste, Recycleye technology incorporates quality control, data management and traceability reporting into its functionality.
With traceability information recorded at the time of identification, MRFs can meet industry standards and maintain accurate processing records, with user-friendly dashboards that allow plant managers to monitor performance, quality and outputs in close to real-time.
Can AI Robots Improve Fibre Line Sorting at Your MRF?
The wide range of benefits associated with AI-powered recycling robots mean that a number of MRFs are embracing this new technology and implementing second generation robotic solutions to maximise efficiency and productivity.
With easy retrofit installation, Recycleye Vision and Recycleye Robotics can be integrated into existing MRFs on fibre and other recycling lines too. To learn more or to discuss your requirements with a member of our team, contact Recycleye here or email us at [email protected].