Browsing by Keyword "Circular Economy"
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Item Compounding process optimization for recycled materials using machine learning algorithms(2022) Lopez-Garcia, Pedro; Barrenetxea, Xabier; García-Arrieta, Sonia; Sedano, Iñigo; Palenzuela, Luis; Usatorre, Luis; Tecnalia Research & Innovation; POLIMEROS; FACTORY; COMPOSITEThe sustainable manufacturing of goods is one of the factors to minimize natural resource depletion and CO2 emissions. In the last decade a big effort has been done to transition from linear economy to circular economy. This transition requires to implement re-manufacturing processes into the current industrial manufacturing framework, replacing the sourcing of raw materials by re-manufacturing technologies. However, this transition is very challenging since it requires the transformation of the companies and more specially their processes, from traditional to circular. To speed up this transformation, the use of tools provided by the 4th industrial revolution are crucial. In particular, the use of artificial intelligence techniques enables the optimization of the re-manufacturing processes and make those optimizations available to all the stakeholders. This paper presents an optimization system for re-manufacturing of recycled fiber through compounding processes with materials that come from composite waste or end of life of products. The proposed approach has been trained with the data collected from several experiments carried out with a compounding machine under different specifications, fiber reinforcement grades, and output material properties. The system will allow to set up a compounding machine for different types of reinforced plastics needless of setting point experiments. The algorithms have been tested with previously unseen scenarios and they have proved to be efficient for giving the optimal material characteristics.Item Monitoring domestic material consumption at lower territorial levels: A novel data downscaling method: A novel data downscaling method(2020-10-01) Bianchi, Marco; Tapia, Carlos; del Valle, Ikerne; Tecnalia Research & Innovation; ECONOMÍA CIRCULARThe availability of harmonized and granular information is critical for the design of place‐sensitive policies toward more sustainable economies. However, accessibility to disaggregated data at subnational levels remains an exception in many geographies and policy domains. In this article, we develop a novel three‐stage—specification, optimization, extrapolation (SOE)—econometric approach to infer harmonized regional level estimates from broadly available socioeconomic data. The approach is tested by estimating domestic material consumption (DMC) in more than 280 European regions (at NUTS 2 level). Unlike previous methods based on similar econometric techniques, our method makes explicit the socio‐metabolic profiles of subnational territories by estimating and applying country‐specific elasticities. Our DMC estimates are consistent with those obtained by ad hoc material flow studies that could be accessed for a sample of regions. The SOE method presented in this paper provides decision‐makers with a powerful tool to explore socio‐metabolic profiles at subnational level and therefore to understand the potential effects of policies aimed at supporting circular economy transitions at such levels. The method can also be adapted with relative ease to support policy designs in other policy areas challenged by severe data scarcity.