NEC and MARUKISANGYO demonstrate efficient recycled plastic production using materials informatics
~ Timerequired to compound and color-match plastic waste halved ~
Tokyo, October 24, 2024 - NEC Corporation (NEC; TSE: 6701) and MARUKISANGYO Co., Ltd. conducted a demonstration experiment in September this year toimprove the efficiency of manufacturing recycled plastic. The experiment appliedmaterials informatics technology using AI to improve the efficiency of materialdevelopment. As a result, the two companies confirmed that the time requiredfor compounding and coloring plastic waste in the production of recycled plasticcan be reduced by half and does not require the expertise of specialized workers.
■Background
Various efforts are being made around the world to reduce plastic waste,which causes environmental pollution and the destruction of nature. Although therecycling and proper disposal of plastics are being promoted around the world, themajority of plastic waste is still disposed of by incineration or landfill.Under these conditions, it is important to accelerate efforts to reuse plasticsas a resource for new products that can help to support a sustainable society.
The plastic recycling process begins with the collection and sorting of plasticwaste. This is followed by crushing, compounding, coloring, and granulation processes,and then the plastic is processed into products called pellets for shipment. Inthe compounding process, the knowledge and experience of skilled workers are especiallyrequired to determine the optimum compound of small amounts and various typesof plastic waste received every day, and to ensure that the pellets are inaccordance with the performance and quantity demanded by the customer, such asstrength, thermoplasticity, and color.
■ About the developed system and the demonstrationexperiment
Based on the compounding data that MARUKI SANGYO has accumulated since itsestablishment, NEC has combined its expertise in the development of materials,such as bioplastics and its materials informatics technology, to develop a systemthat presents compounding and color mixing plans for plastic waste. By enteringthe desired characteristics and color, this system can present the mostappropriate proposal according to the daily fluctuating inventory of plasticwaste.
In thedemonstration test, it was confirmed that the compounding and color mixing planspresented by the system were accurate enough for practical use. It was also confirmedthat the system can reduce the time required to study and determine the compoundingof plastic waste and to study, test, and determine the pigment combinations by approximately33% compared to skilled workers with extensive knowledge and experience, and byapproximately 50% compared to inexperienced workers. This will contribute tothe resolution of issues such as knowledge transfer of skilled workers at plasticsrecycling sites, labor shortages, and inventory management.
■Future Outlook
Based on these results, the two companies have begun discussions to developa solution for the efficient production of recycled plastic. The companies aimto provide consulting-based solutions to companies involved in plasticsrecycling by 2025, promoting the efficient and cyclical use of plastic waste. Inaddition, by making some of the information on the production of recycledplastic available for disclosure, AI will create high added value for recycledplastic materials and contribute to expanding the scope of their use.
By leading these efforts and promoting co-creation activities that transcendindustry boundaries, the two companies will accelerate the circular economy, asocioeconomic system that efficiently circulates resources, and work towardsolving social issues.
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