The robot assistant has just taken hold of the monitor. It is able to distinguish it from other electronic objects such as PCs, smartphones, and tablets that might all pass through its artificial hands, and therefore knows just how to hold them. The robot then gives the item to a member of staff who begins to dismantle it. When all the pieces have been separated – the glass of the monitor, the plastic structure, the electronic circuit board – the robot places them on a conveyor belt that takes them to another area, where the components are analysed to see whether they can be reused, repaired, or in the worst case, disposed of. In the latter instance, the parts head to a final automated workstation where the materials are separated, then shredded or crushed in the case of plastic and glass and sent for recycling. The most complicated part concerns the electronic circuit boards, which contain expensive materials such as copper, or even valuable or strategic resources such as rare-earth metals.
The frontier of “re-manufacturing”
In Milan, Italy, STIIMA, the National Research Council’s Institute for Smart Industrial Technology Systems for Advanced Manufacturing, and the Polytechnic University of Milan have set up a joint experimental “re-manufacturing” and “de-manufacturing” facility. While still at a pilot experimental level, this is an excellent example of the enormous potential of artificial intelligence in the circular economy. This is because there are no similar plants in the world capable of managing electronic waste, understanding what the items are, dismantling them and recovering their useful or valuable components. For this reason, millions of tonnes of old TVs, monitors, broken PCs, telephones, and electrical appliances of every type, are piling up at waste sites, from where they are often taken to fuel an illegal and extremely polluting market. Its real size is difficult to estimate, but according to UNEP, the United Nations Environmental Protection agency, the global market for electronic waste is worth more than 62 billion dollars and only 20% of it is officially recycled. The remainder feeds a business that exports the waste to equatorial Africa, India, and South East Asia - a practice that has an enormous environmental and social impact.
The secret to designing circular products
The way electronic waste is currently managed is just one of many examples of an economy based on a linear process, one which begins with the exploitation of natural resources and culminates in the products’ disposal as waste. This model is no longer sustainable for the planet. It is fundamental therefore to convert to a circular economy, as exemplified by the pioneering de-manufacturing plant in Milan.
The Ellen MacArthur Foundation, an organisation that works around the world to offer examples and share best practices linked to the circular economy, also provides important support for this transition. Through a network of one hundred global businesses, including the Enel Group, the foundation produces documents and tools to help in the spread of circular culture. This tutorial, for example, explains how artificial intelligence can take advantage of its capacity to rapidly analyse enormous quantities of data in order to improve three fundamental aspects in the design of circular products. The first is the ability to identify the best way to design products based on criteria of circularity, considering both the use of raw materials in production and the object’s entire lifecycle. The second is to be able to speed up the design process of a circular product and therefore hasten its arrival on the market. Finally, the third aspect concerns the extent to which AI can contribute to finding new solutions by thinking “out of the box” and begin to create consumer goods in a different way.
For example, AI can be used to predict faults and related problems during the working life of a product, making it more circular through the extension of its useful life. For this reason, at Enel we have adopted and promoted the use of machine learning techniques. These have allowed us to carry out predictive analysis for the maintenance of the electricity distribution grid and components of power stations, flagging problem areas in advance and acting on impending faults to extend the useful life of our assets and, at the same time, improve the quality of the service we provide.
From electronics to the consumption of innovative foods
Examples of this type of approach already exist and are beginning to spread. In a 2019 study published by McKinsey and created with Google and the Ellen MacArthur Foundation, numerous real applications are described, for example in the agriculture and consumer electronics sectors. In the management and sorting of electronic waste, AI systems are used to select batteries or mobile phones from unsorted waste, as Swedish company Refind Technology is doing, for example. Machine learning systems are employed to analyse the images of waste in order to identify electronic items. Solutions of this type have already been developed by companies such as AMP Robotics, Bulk Handling Systems, Sadako Technologies and ZenRobotic.
In the food sector AI is being used to design innovative foods, based on products that can serve as alternatives to meat, fish, dairy and eggs, areas where the production chain has a substantial environmental impact. Examples include the plant-based meat substitutes made by Beyond Meat, which have already arrived in Italian restaurants, those of Impossible Foods, or Spanish company NotCo’s alternatives to milk, ice cream and mayonnaise. But the applications also extend to all of the phases of the agri-food production chain, from farming to packaging.
Thanks to hi-tech, creative and smart solutions, the road towards the circular economy can become a superhighway. In which case the planet will be grateful.