Hyperspectral Imaging: Shaping the Future of Plastic Recycling
A significant value lies in reusable material. However, we are still far away from our recycling targets. Most of the collected waste is still used for energy production and burnt in power plants, not reused. Price is often a factor in low recycling rates, as producing new products from raw materials is often cheaper than recycling materials.
Reusing materials must be cheaper and easier than virgin materials to make recycling ecologically and economically viable. With proper material handling methods, different materials are efficiently recycled and turned into profit. Hyperspectral imaging can make a difference in sorting for recycling.
Current Challenges in Efficient Recycling
A typical waste management process includes the collection of waste in a recovery facility, segregation into different waste fractions, cleaning, and final classification into materials placed in landfills, burned, or recycled based on the type and purity.
The sorting process is a critical step in recycling. Better sorting accuracy means separating different material grades better, resulting in higher value recovery. Typically, sorting processes are based on a mix of techniques and rely not only on one detection technology. The detection technology often limits the types, and the amount of the collected material sorted.
Most recycling plants use different technologies, from bar code readers and RGB cameras to X-ray and Eddy current systems. While they are capable technologies to a certain extent, they are not perfect solutions, as their capability to identify the material is limited.
For example, if a plastic bottle is missing the barcode, it is impossible to detect if it is PET or HDPE. Eddy-current detectors can sort out conductive metals but not separate plastics or pulp. RGB cameras can sort bottles into transparent, black, and colored, but cannot distinguish one plastic type from another.
When the recycled portion is not pure enough for reuse, we lose recyclable material to landfill or energy production. Poor sorting results in lost profits, which makes recycling unprofitable and dependent on public support.
Different waste streams require different detection and processing methods to be recycled efficiently, and current recycling methods are not flexible, efficient, or informative enough to tackle the challenge.
Currently, human labor is behind inadequate detection technologies. Sorting waste by hand is slow, inaccurate, expensive, and dangerous, and separating different plastic types from each other remains impossible because the human eye cannot tell them apart.
Recycling plants must have sensors capable of separating different materials reliably and with high purity to work efficiently, profitably, and safely. Hyperspectral imaging offers a powerful technology for accurate and sustainable waste recycling.
How Hyperspectral Cameras Can Improve Recycling Efficiency?
Hyperspectral cameras can differentiate materials accurately and reliably based on their chemical composition. They measure and analyze the spectrum of light reflected from or transmitted through the material. When measuring the spectrum beyond the visible region, called near-infrared (NIR), we see that chemically different materials have unique spectra.
Multispectral technology has improved the situation; however, it has its limitations. Multispectral cameras typically acquire spectral data with one to three, or in some cameras, a maximum of 8 spectral bands, meaning that in each sorting location, they identify only a few basic materials. The purity of the result is also often limited, as there are interfering factors in the material stream. (Read more about the difference between multispectral and hyperspectral cameras.)
Hyperspectral imaging is rapidly transforming waste sorting, thanks to recent breakthroughs in camera technology and data processing. While earlier adoption had some limitations, such as speed, spatial resolution, ruggedness, connectivity, and cost, recent advancements have significantly overcome these barriers.
Today’s hyperspectral cameras offer enhanced speed and resolution, while their implementation cost meets commercial solutions’ ROI criteria. Additionally, algorithms and real-time data processing capabilities are now readily available, enabling efficient handling of the vast data volumes generated. These innovations pave the way for widespread, effective deployment of hyperspectral imaging in waste management.
A line-scan hyperspectral camera is a practical and excellent working solution for in-line sorting applications, as it captures the entire spectral data of the full material stream from each pixel in the line precisely, simultaneously with a single scan.
Today, you can install line-scan hyperspectral cameras on existing and new sorting lines with proper illumination and a real-time data processing solution like any line-scan camera. The material identification result, pixel by pixel, is available to commercial machine vision systems through a standard interface. The results can control the air nozzles or the picking robots.
A hyperspectral camera solution provides superior performance and several benefits in various waste treatment processes over conventional sensor technologies, as summarized in Table 1.
Table 1. Added value by hyperspectral imaging in sorting different types of waste streams
Hyperspectral cameras increase sorting accuracy by providing precise information on material type. The latest generation of hyperspectral cameras can increase the purity of recycled materials by close to 100 %. Increasing the purity of recycled plastic by even a few percent can double its value. Extracting more recyclable material also means we dispose of less waste in landfills.
Compared to a multispectral camera with fixed spectral bands, the hyperspectral camera is flexible and can adapt to sorting various waste streams. It can also adopt new sorting algorithms when they become available.
Benefits Of Hyperspectral Imaging in Plastic Recycling
Out of all the plastic manufactured, only 9% gets recycled. 12% are incinerated for energy, and 79% go to landfills or nature. Most non-recyclable plastic waste comes from being unable to separate different plastic types from each other reliably.
When we sort and separate plastic, high-quality and valuable polymers can be reused. The main objective in sorting is to reduce the quantity of non-targeted plastic polymers and the number of non-plastics like paper, metal, glass, oil, soil, or other contaminants. There may also be unwanted additives like flame retardants within the plastic that can be detected, identified, and sorted with hyperspectral cameras.
Different polymers have identifiable spectral signatures in the NIR spectral region by which to sort. However, many of the spectral signatures are close to each other. The hyperspectral camera’s high spectral resolution is key to high sorting accuracy. For example, PP, PE, and PET plastics can achieve nearly 99% purity
Sorting of Black Plastics with Hyperspectral Cameras
A large fraction of recyclable plastic consists of black plastics, often found in the automotive and electronics industries, which have added carbon-based pigment to produce the dark grey or black color. Black plastic types have been notoriously difficult to identify, and so far, there has been no reliable sensor technique to sort these materials for reuse. Even NIR hyperspectral cameras struggle, as the black carbon-based pigment absorbs practically all the NIR light.
In addition to the NIR region, different plastics have characteristic spectral features in the longer infrared region called mid-wave infrared (MWIR), where most black pigments are ‘less black’ (less absorbing) than in the NIR region. Thus, MWIR light can penetrate and reflect from black materials, making their spectral identification possible.
With the Specim FX50 hyperspectral camera that operates on the MWIR region, we can sort black ABS plastics with close to 99 % purity. It is the only hyperspectral camera currently on the market operating in the MWIR region with the required speed, resolution, and sensitivity for industrial in-line use.
Below is an example of black plastic sorting measured in a laboratory with a Specim FX50 hyperspectral camera. Twelve pieces of ABS and PE were measured along with ten pieces of PS (34 altogether). Half of the samples were shiny for each group, and the other half had diffuse surfaces. The figure below shows that samples of ABS, PS, and PE could be accurately sorted with the Specim FX50.
Hyperspectral Imaging Shapes the Future of Recycling
Improved sorting accuracy increases the purity and value of the recycled material and the reused waste percentage. Better detection systems are needed to improve sorting accuracy.
The potential impact of hyperspectral imaging on the recycling industry and society is significant. The hyperspectral camera is an accurate, reliable, non-destructive, and contactless detection tool that improves operational efficiency, material purity, and profitability.
Advanced hyperspectral camera technology, analysis software, and spectral libraries are already available and in use in modern recycling machines and waste-sorting facilities and are expected to grow in the future due to the growing need to solve previously unfeasible sorting tasks.
