Applying Artificial Intelligence and Computer Vision to Open Source Distributed Recycling and Additive Manufacturing of Waste Plastic

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People will recycle for money. In places where cash is offered for cans and bottles, metal and glass recycling has been a great success. Sadly, there are fewer cash incentives for recycling plastic and only 9% of plastic waste is recycled. The rest pollutes landfills or the environment. But now, several technologies have matured that allow people to recycle waste plastic directly by 3D printing it into valuable products, at a fraction of their normal cost. People are using their own recycled plastic to make decorations and gifts, home and garden products, accessories and shoes, toys and games, sporting goods and gadgets from millions of free designs. This approach is called distributed recycling and additive manufacturing, or DRAM for short. The first step in DRAM is to sort and wash the plastic with soap and water. Next, the plastic needs to be ground into particles. Then the particles are either turned into 3D printer filament using recyclebots (waste plastic extruders), and used on low-cost 3D printers or it is directly 3D printed by fusing particles. Our research has shown DRAM is not only better for the environment, but it is also highly profitable for people making their own products. Using open source designs to produce your own products is more cost-effective than purchasing them. If you used recycled plastic you can save over 99% from the commercial equivalent. This is exciting, however DRAM is limited, and is currently only used by technically-savvy first adopters because of five challenges: 1) There is no easy way to identify if plastic can be used for DRAM, 2) there is no low-cost method of shredding thin plastic like PET water bottles at home, 3) recyclebots make bad filament from non-uniform waste feedstocks, 4) low-cost 3D printers suffer from a range of failures for exact digital replication of designs, and 5) large 3D printers are prohibitively expensive and fail more often. The long-term objective of this research program is to overcome these five challenges related to the upcycling plastic and other wastes into final products in open source DRAM systems by: 1) developing a low-cost rapid method to evaluate waste for DRAM based on an open source melt flow index; 2) developing a desktop energy-efficient mostly 3D printable shredder capable of rendering thin plastic containers to flakes; 3) integrating a computer vision automatic feedback system to control recyclebot-extruded 3D printing filament from waste materials so it can be made more uniform; 4) integrating an open source artificial intelligence program and computer vision to fix 3D printing errors in real time; and 5) using recyclebots as printers for hanging cable 3D printers. All together this smart DRAM system will help drive the cost and complexity of DRAM down so that everyone including those living in an isolated and remote communities, indigenous or those doing military/humanitarian deployments - can easily use waste plastic to make products that they need.