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Supporting the Selection of Quality Tools Using Neural Networks

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Advances in Production (ISPEM 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 790))

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Abstract

Quality management tools are well-grounded in the management of enterprises regardless of an adopted quality management concept. A crucial problem to be solved is the provision of support for the selection of these tools in such a way as to choose the most useful one. The article presents an overview of traditional solutions for the selection of quality tools and their computer-aided choice. The analysis of the source literature showed a research gap regarding solutions for automatic support for the selection of quality tools. In order to resolve this problem, neural networks were used, specifically a feedforward multilayer network with backward propagation of errors. Data were prepared in the form of learning examples and many classification models based on the selected neural network were developed. As a result, the best model with the highest classification effectiveness was selected. Such a classification model can be placed in an expert system, which can then support a less experienced employee in the selection of quality tools (e.g. in the quality assurance department in an enterprise).

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Author information

Authors and Affiliations

  1. Faculty of Mechanical Engineering, Poznan University of Technology, M. SkƂodowska-Curie Square 5, 60965, Poznan, Poland

    Beata StarzyƄska

  2. Faculty of Computer Science, Kazimierz Wielki University, Chodkiewicza 30, 85064, Bydgoszcz, Poland

    Izabela Rojek

Authors
  1. Beata StarzyƄska
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  2. Izabela Rojek
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Corresponding author

Correspondence to Izabela Rojek .

Editor information

Editors and Affiliations

  1. Wroclaw University of Science and Technology, WrocƂaw, Poland

    Anna Burduk

  2. Liverpool John Moores University, Liverpool, UK

    Andre Batako

  3. School of Engineering, University of Minho, GuimarĂŁes, Portugal

    José Machado

  4. Katedra Budowy Maszyn, Politechnika ƚląska, Gliwice, Poland

    Ryszard WyczóƂkowski

  5. Rzeszow University of Technology, RzeszĂłw, Poland

    Katarzyna Antosz

  6. Lublin University of Technology, Lublin, Poland

    Arkadiusz Gola

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StarzyƄska, B., Rojek, I. (2023). Supporting the Selection of Quality Tools Using Neural Networks. In: Burduk, A., Batako, A., Machado, J., WyczóƂkowski, R., Antosz, K., Gola, A. (eds) Advances in Production. ISPEM 2023. Lecture Notes in Networks and Systems, vol 790. Springer, Cham. https://doi.org/10.1007/978-3-031-45021-1_10

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