What are the digital and technological innovations put in place by the players in the transformation and recovery of waste sector?
Predictive maintenance and intelligent waste collection
The strategic committee of the Transformation and recovery of waste sector unveiled last year the new contract for the sector with ambitious projects to support the sector in its transformation.
This sector, made up of actors positioned on collection, sorting, preparation, recovery and recycling activities, finds itself faced with the need to place its waste management activities more in line with a saving logic circular in order to meet the challenges of ecological transition and the objectives set by the regulatory and legal framework.
The Energy Transition Law for Green Growth and the Circular Economy Roadmap plan to reduce landfill by 50% between 2010 and 2025, thus reinforcing the need to initiate the transformation of the sector in order to improve performance.
The contract of the strategic committee of the sector which signs a commitment between the State and the actors of the sector outlines its contours, in particular by highlighting robotization and data collection.
There are many avenues of innovation with the integration of digital technologies, such as artificial intelligence, connected objects and even 3D printing.
What are the digital and technological innovations put in place by actors in the transformation and recovery of waste sector?
Robotisation and AI at the service of sorting centers
Demand for raw materials has become very complex. Indeed, where 6 chemical elements of Mendeleev’s classification were needed to build a mill, today it takes 60 to build a wind turbine.
Faced with this observation, the sector must innovate in order to take into account these new requirements and constraints and therefore to modernize its sorting centers. Experiments are going well and the robotic triptych, artificial intelligence and digital innovations opens the way to a new generation of sorting centers.
France installed a robot in an Amiens factory to increase the amount of sorted waste and the quality of selection. A first step in its installation consisted of sending hundreds of thousands of photos to its database. The robot was therefore able to distinguish paper and cardboard from cans and plastic bottles to be removed from the sorting stream.
During the second stage of its initialization, it was necessary to adapt the algorithm based on artificial intelligence and deep learning so that the robot is even more precise and learns from its errors. At cruising speed, the robot removes sorting flow 60% more waste per hour than an operator.
To ensure quality control after sorting by the robot, an operator from the waste management company, equipped with a tablet, remains present at the end of the chain to collect the 10% of waste forgotten by the robot. Via the tele-operated sorting, the operator indicates on his tablet the waste to be removed from the treadmill and an articulated arm comes out of the flow.
The implementation of this type of intelligent sorting robots, equipped with learning mechanisms for recognizing the different wastes whose acquired knowledge would be shared with all the sorting operators in the territory, constitutes an important development issue on which to rely. the sector’s strategic committee.
Predictive maintenance and intelligent waste collection
Sorting is not the only area of the transformation and recovery sector to benefit from digital and technological innovations. The Energy Recovery Units (incinerators) and landfill sites have implemented computer-assisted maintenance management software for the past few years to help technicians trace their maintenance interventions.
Cross-referenced with data from connected objects installed on the equipment, manufacturers want to move towards predictive maintenance to better anticipate the need for spare parts, the mobilization of specialists and no longer act in an emergency, thus guaranteeing better safety of the intervening technicians.
Connected objects also make it possible to optimize waste logistics and in particular waste collection. A company has set up a connected waste management center near Lyon.
By centralizing the data from the sensors located on the garbage collection trucks and on the dumpsters and crossing them with the garbage collection areas required by their customers, the pilot center teams select the best collection route offered by the optimization algorithm.
The deployment of type of sensors will gradually generalize the concept of connected trash which, thanks to the collected data of big data type such as the filling rate or the composition of waste, will optimize the management of the collection service and improve sorting performance.
The transformation and recovery of waste sector faces many challenges: falling raw material prices, deteriorating margins, the appearance of new players and new rules. The stakes are high for the historical actors of the sector who will have to find in the technological and digital innovations a new circular economic model in order to become a leader of the ecological transition.
It will be a question for the State, the local communities and the companies of finding a good calibration in order to invest massively in equipment and infrastructures integrating the new technologies and to anticipate the future processes of construction of the trades and skills of tomorrow. It is thanks to the agreement of all the stakeholders that we will be able to build a world for our children.