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Analyzing Industry 4.0 Models with Focus on Lean Production Aspects

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 311))

Abstract

Nearly all enterprises have to face enormous challenges when dealing with digitalization topics such as Industry 4.0/Industrial Internet. To support companies to handle these challenges and therefore, to be able to “move” in an Industry 4.0 environment several frameworks or reference models already exist. Within this paper we provide results of a detailed analysis of selected Industry 4.0 models. However, we show that not all models are dealing with this topic in a holistic way but rather focusing on specific aspects or requirements of Industry 4.0. Additionally, we focus in our analysis on lean production aspects since the basic principles of lean management/lean production offer since the 1980s appropriate measures to optimize production and therefore, can be/should be addressed by Industry 4.0 models as well. Hence, it became obvious that those principles are not often addressed in Industry 4.0 models. Despite the fact that those aspects are often seen as a basis for Industry 4.0 implementation this is mostly not integrated in the respective models. Therefore, the contribution of our paper consists of the classification of 31 Industry 4.0 models/frameworks as well as the identification of needs for further research to enhance existing Industry 4.0 models to a more holistic approach.

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Correspondence to Christian Leyh .

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Appendix

Appendix

Additional possibility to download the assessment of all articles and the respective reference list: https://tu-dresden.de/bu/wirtschaft/isih/ressourcen/dateien/isih_team/pdfs_team/Supplementary-Material.pdf.

Table 4. Categorization of the identified articles according to the classification criteria
Table 5. List of identified articles

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Leyh, C., Martin, S., Schäffer, T. (2018). Analyzing Industry 4.0 Models with Focus on Lean Production Aspects. In: Ziemba, E. (eds) Information Technology for Management. Ongoing Research and Development. ISM AITM 2017 2017. Lecture Notes in Business Information Processing, vol 311. Springer, Cham. https://doi.org/10.1007/978-3-319-77721-4_7

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  • DOI: https://doi.org/10.1007/978-3-319-77721-4_7

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-77721-4

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