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Methods of Data Mining for Quality Assurance in Glassworks

Abstract : In manufacturing enterprises implementing the idea of Industry 4.0, devices that generate data are increasingly used. Over time, huge data sets are created. These collections, known as Big Data, are very important to the company because they can contain valuable information. One of the goals of today’s enterprises is to discover this information and transform it into knowledge. The aim of the article is to present the methodology of exploration of large data sets from the manufacturing process in glassworks. The result of the research is knowledge about the parameters of the manufacturing process causing defects in the products.
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Submitted on : Friday, February 14, 2020 - 10:03:25 AM
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Łukasz Paśko, Paweł Litwin. Methods of Data Mining for Quality Assurance in Glassworks. 20th Working Conference on Virtual Enterprises (PRO-VE), Sep 2019, Turin, Italy. pp.185-192, ⟨10.1007/978-3-030-28464-0_17⟩. ⟨hal-02478736⟩

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