Compounding process optimization for recycled materials using machine learning algorithms
Author/s
Lopez-Garcia, Pedro; Barrenetxea, Xabier; García-Arrieta, Sonia; Sedano, Iñigo; Palenzuela, Luis; [et al.]Date
2022Keywords
Compounding
Recycled fiber
Remanufacturing
Optimization
Machine Learning
Circular Economy
Abstract
The 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 ...
Type
conference output