Industry 4.0 - The Way to a Digitised Production Company

Der Weg zu einem digitalisierten Produktionsunternehmen

Jürgen Köbler, Tobias Fischer, Benjamin Klerch, Michael Schlecht
JournalIndustrie 4.0 Management
Issue Volume 36, 2020, Edition 3, Pages 57-60
Open Accesshttps://doi.org/10.30844/I40M_20-3_S57-60
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Abstract

The age of globalisation is characterised by increased competition. An opportunity to succeed in the face of increasing competition lies in the digitisation of production companies. This article is dedicated to the design of a three-stage model platform of Industry 4.0, which focuses on the consistency of processes from the customer to the supplier at all company levels. The model platform is followed by an overview of the transformation steps for evaluating and shaping progress on the way to become a digitised production company.

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Bibliography

[1] Kagermann, H.; Wahlster, W.; Helbig, J.: Umsetzungsempfehlungen für das Zukunftsprojekt Industrie 4.0: Abschlussbericht des Arbeitskreises Industrie 4.0. Frankfurt (2013).
[2] Kaufmann, T.; Forstner, L.: Horizontale Integration der Wertschöpfungskette in der Halbleiterindustrie. In: Handbuch Industrie 4.0. Berlin, Heidelberg (2016).
[3] VDI-Richtlinie 3405 Blatt 2.1: Additive Fertigung. Laser-Strahlschmelzen metallischer Bauteile Materialkenndatenblatt Aluminiumlegierung. AlSi10Mg. (2017).
[4] Junk, S.; Klerch, B.; Hochberg, U.: Structural Optimization in Lightweight Design for Additive Manufacturing, Procedia CIRP 84, S. 277–282 (2019).
[5] Müller, R. u. a.: Handbuch Mensch-Roboter-Kollaboration. München (2019).
[6] Bächler, A. u. a.: Systeme zur Assistenz und Effizienzsteigerung in manuellen Produktionsprozessen der Industrie auf Basis von Projektion und Tiefendatenerkennung. In: Zukunft der Arbeit: Eine praxisnahe Betrachtung. Berlin, Heidelberg (2017).
[7] acatech: Cyber-Physical Systems: Innovationsmotor für Mobilität, Gesundheit, Energie und Produktion. München (2011).
[8] VDI: Cyper-Physical Systems. Berlin (2013).
[9] Köhler-Schute, C.; Amberg, J.: Industrie 4.0: Ein praxisorientierter Ansatz. Berlin (2015).
[10] Qi, Q. u. a.: Digital Twin Service Towards Smart Manufacturing: 51st CIRP Conference on Manufacturing Systems. S. 237- 242 (2018).
[11] Vieira, A. A. C.: Setting an Industry 4.0 Research and Development Agenda for Simulation: A Literature Review. S. 377–389 (2018).
[12] Kollmann, T.: E-Business: Grundlagen elektronischer Geschäftsprozesse in der digitalen Wirtschaft. Berlin, Heidelberg (2019).

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