In the span of COP26, many environmental issues have been raised and recycling optimization stood out as one of the biggest challenge to achieve. Sorting domestic waste bins can already be quite messy, both for individuals and for sorting centers; so imagine what it is like when it comes to recycling cars, that bring together more than 30 000 different parts in many different materials.
Stakes and expectations are very high as car manufacturing belongs to the carbon intensive industry club. While the World seeks new ways to reduce carbon emissions and fights climate change, the car industry is already projected to save over a billion tonnes in emissions and add nearly $500 billion to global GDP by 2030. To stem that number, the European Commission has set a End of Live Vehicle Directive, claiming that each vehicle produced by manufacturers has to be re-used, recovered or recycled at 95% (the rate set previously by the EU was 85%)
To meet these new recycling standards, the industry must find innovative processes and improve both end of live vehicle (ELVs) processing and recyclable parts detection. Computer vision strikes as a game changing solution for the whole recycling industry.
There are 2 steps where computer vision can be a real game changer for this industry: car evaluation before dismantling and components sorting after dismantling.
Evaluating and sorting cars before dismantling
To ensure the best recycling outcome, the stake of ELV dismantling and recycling is not just recycling materials, it’s also identifying what parts of the vehicle are still good to be reused, for example in the auto repair market.
That is what we are focusing on at Monk with our recycler partners. Our solution answers three key objectives :
- Quoting and buying ELVs accurately
Leveraging Monk’s AI powered vehicle inspection technology, car recyclers have an instant overview of a vehicle’s condition and assets. Thereby, they can buy it at the most accurate price and never miss an opportunity.
- Identifying the re-usable parts
Using our trained AI models, car recyclers can instantly know which car parts are still intact, which are damaged with a severity grading. This instant overview helps them streamline operations and organize dismantling according to inventory needs.
- Managing inventory efficiently :
With our AI powered vehicle inspection, recyclers can identify the usable parts and easily match with the spare part demand at scale, leading to greater profitability from ELVs for salvage and less waste for the planet.
Sorting and recycling components post dismantling
To meet the European Commission’s objectives, the car industry stakeholders must invest in industrial sorting & recycling facilities for car components.
Since vehicles are made from up to 30 000 different parts, sorting operations have to be extremely precise and cost-effective, that’s an issue only state-of-the-art AI technology can solve.
Let’s draw a parallel with the household waste recycling methods. As of today, most of the sorting operations rely on industrial machine vision technologies in closed environments where light and motion are constrained. The objects are already known and the observed events are predictable.
To deal with unknown objects which are often in uncontrolled environments, computer vision is necessary. Lixo, a french startup is using computer vision models to analyze waste flows in real time and continuously, to better recover them, limit the volumes buried and improve the competitiveness of the recycling industry.
Computer vision and car dismantling
Therefore, we advocate that computer vision should be used in a similar way for car pre-recycling, sorting any small components in a car. Leveraging such technology, car dismantlers can maintain strong cost-efficiency, improve recycling capabilities for every vehicle scrapping and eventually help the car manufacturing industry meet with the European Commission Objectives.
