Abstract
The textile industry in Europe is facing a new challenge in order to stay competitive into the textile market. They need to be flexible, cost efficient and produce with high quality. The setting of the machinery parameters is therefore an important aspect that combines implicit knowledge of workers and engineers with explicit knowledge. This makes it an ideal domain for CBR. It is used for an automatic parameter setting but the data cannot be reduced to a flat representation, as yarns and fabrics are multicomponent artefacts. Therefore we propose a combination of 4 algorithms to evaluate the similarity of the yarns. The application was successfully applied for spinning and it can be applied in the following steps of the textile processes like weaving.
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Sevilla-Villanueva, B., Sànchez-Marrè, M., Fischer, T.V. (2014). Estimation of Machine Settings for Spinning of Yarns – New Algorithms for Comparing Complex Structures. In: Lamontagne, L., Plaza, E. (eds) Case-Based Reasoning Research and Development. ICCBR 2014. Lecture Notes in Computer Science(), vol 8765. Springer, Cham. https://doi.org/10.1007/978-3-319-11209-1_31
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DOI: https://doi.org/10.1007/978-3-319-11209-1_31
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