GreenTech is one of the largest PET waste recyclers in Europe, with facilities in Romania, Slovakia, and Lithuania.
In addition to recycling various types of PET, GreenTech manufactures secondary raw materials like PET flakes, food-grade pellets, and polyester fibers. Sectors as varied as the automotive industry, construction and textiles use those products, making the company a key driver of circularity in Europe.
GreenTech’s multinational AI strategy was designed to address different challenges in different facilities: In Slovakia and Romania, GreenTech’s team uses Greyparrot Analyzer to monitor infeed material, negotiate with suppliers and maximise yields.
Despite those differences, each facility’s team uses AI to solve a fundamental challenge: a lack of visibility into complex waste streams.
The challenge: Keeping track of inconsistent supplier material
GreenTech’s plastics recovery facilities (PRF) in Slovakia and Romania buy material from a range of suppliers — paying a premium for batches with fewer contaminants. One of Quality Control Manager Gabriela Fabryova’s responsibilities is to make sure that they’re getting what they pay for:
We buy material at different quality grades, but the grading isn’t always accurate. Two batches of PET could look the exact same from the outside, but one could be full of textile contaminants, for example.”
– Gabriela Fabryova, Quality Control Manager at GreenTech Slovakia
With a small team of around five staff, Gabriela could only assess 50 kilograms of material per bale, taking advantage of weekly maintenance downtime. That wasn’t enough to determine whether suppliers were meeting GreenTech’s quality standards:
Manual sampling helped us spot extreme contamination, but we didn’t have a full understanding of the material we were putting on our sorting lines, or whether our blends were helping us meet our targets.”
– Gabriela Fabryova, Quality Control Manager at GreenTech Slovakia
In Romania, Process Manager Marian Hornet encountered a similar challenge — manual analysis couldn’t keep up with the sheer scale of infeed material his facility processes:
“Between receiving material and understanding its quality, we usually have a delay of about four hours. In that case, it may already be too late to make adjustments.”
– Marian Hornet, Process Manager at GreenTech Romania
Blending material more effectively, managing supplier relationships and investigating dips in final product quality are all essential tasks for Gabriela and Marian. Those tasks relied on data that they didn’t have — until GreenTech embraced waste intelligence technology.
The solution: Automated infeed monitoring
To fill that data gap, GreenTech installed a single Greyparrot Analyzer unit in each facility to monitor supplier material composition.
Gabriela now uses the same scheduled downtime to assess supplier material with Greyparrot AI. Instead of 50 kilogram manual samples, she now tracks every single object that GreenTech buys from suppliers via the Analyzer portal’s live dashboards.
Marian accesses infeed data the same way, using it to get live insight into the quality of material arriving at the facility.
That simple change has completely transformed the way each facility monitors supplier material and manages infeed blending.
The outcome: Higher quality products at lower costs
Since deploying the Analyzer system, GreenTech has fully embraced automated waste analysis — making savings and quality improvements in the process:
✅ Reducing sampling costs, and optimising time management
With just one unit, Gabriela has changed the way she assesses material:
We’ve reduced the manual sampling that we do in the facility. We previously determined the quality of infeed stock by hand, but we now get faster, better results with Greyparrot.”
– Gabriela Fabryova, Quality Control Manager at GreenTech Slovakia
GreenTech’s Romanian facility has also transformed their sampling process. Now, Marian only requests manual samples in extreme cases:
After deploying Greyparrot Analyzer, we only do sampling when we have serious doubts about material quality.”
– Marian Hornet, Process Manager at GreenTech Romania
✅ Managing supplier negotiations
Like Jessica, Gabriela and Marian believe that detailed infeed data has a knock-on effect on the entire sorting process. The GreenTech team have begun to use Analyzer to guide the blending process, and maximise yield:
Another huge benefit is that we now know what we’re actually putting onto our sorting lines — and whether our blends are helping us meet our targets for yield and quality.”
– Gabriela Fabryova, Quality Control Manager at GreenTech Slovakia
In Romania, Analyzer data is helping Marian differentiate between individual types of PET bottle, which can change the way he blends material and adjusts sorting machinery:
AI can help us evaluating the weight of PET bottles based on the specific density of the bottles, since bottles from different countries have different wall thicknesses.”
– Marian Hornet, Process Manager at GreenTech Romania
✅ Investigating sorting challenges
When things don’t go to plan, Gabriela now has all the information she needs to find out where blends could have improved, or where supplier material caused unwanted contamination:
For me, it’s easier to investigate why we may not have met the yield we expected to, because the material we bought was not as good as we might have expected.
It’s easier to understand what’s gone wrong in the whole process.”– Gabriela Fabryova, Quality Control Manager at GreenTech Slovakia
The future: Deploying AI beyond infeed monitoring
After deploying Analyzer units at facilities across Europe, GreenTech’s team are already identifying new opportunities to maximise profitability with AI.
Gabriela is no exception: in the short term, she wants to put the power of real-time waste data in the hands of her team as they blend material for sorting:
A monitor on the buffer (where material gets mixed) would help our team see the impact of blending as soon as they add new material.
They might see that a batch contains more light blue plastic than it should, then remove light blue material from future material to balance things out, for example.”– Gabriela Fabryova, Quality Control Manager at GreenTech Slovakia
It’s an idea that’s already making real-world impact: at Greyparrot, we’ve already seen customers like Re-Gen install monitors directly on their machinery to display Analyzer dashboards. When something changes, line staff can take immediate action.
Embracing facility-wide monitoring
GreenTech’s Slovakian and Romanian facilities have taken a major step towards more automated, profitable resource recovery by automating infeed analysis. Their colleagues in Lithuania have made similar gains by keeping track of outfeed quality.
The facilities may soon apply each other’s learnings to create a single, intelligent recovery process:
With another Analyzer unit on our output line, I could see how many contaminants are making it through the sorting process.
That would make it easier to track sorting efficiency, and final product quality.”– Marian Hornet, Process Manager at GreenTech Romania
Learn how more waste management leaders are using AI to boost efficiency (and profits) here.
