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Lean Manufacturing Knowledge Correlation Model

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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

This article describes the results of a statistical study based on data collected in a survey. The questionnaire survey conducted at one of the Polish plants of an international automotive corporation was designed to investigate the level of knowledge, attitudes and awareness towards issues related to production management systems. Statistical analysis derives the correlations occurring in the “knowledge” subgroup of the data, and a substantive expert study was conducted based on the results. In the study, in addition to describing the correlations captured, a description is undertaken of how to improve the performance of areas with the weakest knowledge level scores using the correlations detected.

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Author information

Authors and Affiliations

  1. Silesian University of Technology, 44-100, Gliwice, Poland

    Iwo Podloch

  2. Magna International, 47-225, Kędzierzyn-Koźle, Poland

    Iwo Podloch & Krzysztof Nowacki

  3. Silesian University of Technology, 40-019, Katowice, Polska

    Krzysztof Nowacki

Authors
  1. Iwo Podloch
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  2. Krzysztof Nowacki
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Corresponding author

Correspondence to Krzysztof Nowacki .

Editor information

Editors and Affiliations

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

    Anna Burduk

  2. Liverpool John Moores University, Liverpool, UK

    Andre Batako

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

    José Machado

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

    Ryszard Wyczółkowski

  5. Rzeszow University of Technology, Rzeszów, Poland

    Katarzyna Antosz

  6. Lublin University of Technology, Lublin, Poland

    Arkadiusz Gola

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Podloch, I., Nowacki, K. (2023). Lean Manufacturing Knowledge Correlation Model. In: Burduk, A., Batako, A., Machado, J., Wyczółkowski, 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_14

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