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2023 | OriginalPaper | Chapter

Improving Production System Flexibility and Changeability Through Software-Defined Manufacturing

Authors : S. Behrendt, M. Ungen, J. Fisel, K.-C. Hung, M.-C. May, U. Leberle, G. Lanza

Published in: Production at the Leading Edge of Technology

Publisher: Springer International Publishing

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Abstract

Caused by the trend of shorter product lifecycles, higher numbers of product variants and volatile markets, production systems face increasingly short periods with unchanged requirements. Therefore, the capability of manufacturing systems to reconfigure fast and cost-efficiently to changed requirements becomes a crucial factor for companies to maintain their competitiveness. Currently, reconfigurations of manufacturing systems are, on the one hand, limited due to technical constraints of the used hardware and software. On the other hand, reconfigurations require a lot of time due to manual engineering processes, planning procedures and inefficient deployment of changed production system configurations. Well-known response mechanisms for reducing reconfiguration efforts are the concepts of flexibility and changeability. This paper shows how the challenges of applying these concepts, such as managing complex modular systems or handling high reconfiguration frequencies, can be addressed with introduction of a new approach. With the paradigm shift towards software-defined manufacturing, the full potential of flexibility and changeability can be accessed. Software-defined manufacturing allows to largely decouple the production task from the operating production hardware and to manage the configuration of the production system via a continuous and highly digitized adaption process. By exploiting technologies like data mining and digital twins, the digital planning process determines new configurations of the production that fulfill changed requirements. Subsequently, the new configuration can be validated and procedures for the deployment to the production system can be determined.

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Abele, E., Reinhart, G.: Zukunft der Produktion – Herausforderungen, Forschungsfelder, Chancen.1st end. Carl Hanser Verlag, München (2011)

Mehrabi, M.G., Ulsoy, A.G., Koren, Y., Heytler, P.: Trends and perspectives in flexible and reconfigurable manufacturing systems. J. Intell. Manuf. 13, 135–146 (2002)CrossRef

Cisek, R., Habicht, C., Neise, P.: Gestaltung wandlungsfähiger Produktionssysteme. Zeitschrift für wirtschaftlichen Fabrikbetrieb 97(9), 441–445 (2002). https://doi.org/10.3139/104.100566CrossRef

Bennett, N., Lemoine, G.J.: What a difference a word makes: Understanding threats to performance in a VUCA world. Bus. Horiz. 57(3), 311–317 (2014). https://doi.org/10.1016/j.bushor.2014.01.001CrossRef

Koren, Y., et al.: Reconfigurable Manufacturing Systems. CIRP Ann. 48(2), 527–540 (1999). https://doi.org/10.1016/S0007-8506(07)63232-6CrossRef

Benfer, M., Peukert, S., Lanza, G.: A Framework for Digital Twins for Production Network Management. Procedia CIRP 104, 1269–1274 (2021). https://doi.org/10.1016/j.procir.2021.11.213CrossRef

Heilala, J., Voho, P.: Modular reconfigurable flexible final assembly systems. Assem. Autom. 21(1), 20–30 (2001). https://doi.org/10.1108/01445150110381646CrossRef

Wiendahl, H.-P., et al.: Changeable Manufacturing - Classification. Design and Operation. CIRP Annals 56(2), 783–809 (2007). https://doi.org/10.1016/j.cirp.2007.10.003CrossRef

ElMaraghy, H.A.: Flexible and reconfigurable manufacturing systems paradigms. Int. J. Flex. Manuf. Syst. 17(4), 261–276 (2006). https://doi.org/10.1007/s10696-006-9028-7CrossRefMATH

10.

Stähr, T.J.: Methodik zur Planung und Konfigurationsauswahl skalierbarer Montagesysteme - Ein Beitrag zur skalierbaren Automatisierung. Dissertation, Karlsruher Institut für Technologie (KIT), Karlsruhe (2020)

11.

ElMaraghy, H. A.: Reconfigurable Process Plans For Responsive Manufacturing Systems. In: P. F. Cunha & P. G. Maropoulos (Eds.), Digital enterprise technology: Perspectives and future challenges (pp.35–44). Springer. https://doi.org/10.1007/978-0-387-49864-5_4 (2007)

12.

Nyhuis, P.: Wandlungsfähige Produktionssysteme, GITO Verlag, Berlin. ISBN: 9783942183154 (2010)

13.

Leachman, R.C., Benson, R.F., Liu, C., Raar, D.J.: Impress: An Automated Production-Planning and Delivery-Quotation System at Harris Corporation - Semiconductor Sector. Interfaces 26(1), 6–37 (1996). https://doi.org/10.1287/inte.26.1.6CrossRef

14.

Lechler, A., Kircher, C., Verl, A.: SDM – Software Defined Manufacturing. wt Werkstatttechnik online 2018(5), 307–312. https://doi.org/10.37544/1436-4980-2018-05-33 (2018)

15.

Thames, L., & Schaefer, D.: Software-defined cloud manufacturing for industry 4.0. Procedia cirp, 52, 12–17 (2016)

16.

Neubauer, M.; Ellwein, C.; Frick, F.; Fisel, J.; Kampert, D.; Leberle, U.; May, M.; Behrendt, S.; Esslinger, E.; Pfeifer, D.; Zahn, P.: Kontinuität als neues Paradigma. Computer&Automation (04) (2022)

17.

Fisel, J.: Veränderungsfähigkeit getakteter Fließmontagesysteme: Planung der Fließbandabstimmung am Beispiel der Automobilmontage (2019)

18.

Wiendahl, H.-P.; Reichardt, J. & Nyhuis, P.: Handbuch Fabrikplanung: Konzept, Gestaltung und Umsetzung wandlungsfähiger Produktionsstätten, Carl Hanser, München. ISBN: 9783446437029 (2014)

19.

Abele, E.; Liebeck, T. & Wörn, A.: „Flexibilität im Investitionsentscheidungsprozess“, wt Werkstattstechnik online, Vol. 97, 1/2, 85 f. (2007)

20.

Zäh, M. F.; Möller, N. & Vogl, W.: Symbiosis of changeable and virtual production - the emperor’s new clothes or key factor for future success. In: Proceedings (CD) of the international conference on changeable, agile, reconfigurable and virtual production, München (2005)

21.

Schuh, G.: Produktionsplanung und -steuerung. Grundlagen, Gestaltung und Konzepte, Springer-Verlag Berlin Heidelberg, Berlin, Heidelberg. ISBN: 978–3–540–40306–7 (2006)

22.

Hax A.C., H.C. Meal: Hierarchical integration of production planning and scheduling M.A. Geisler (Ed.), Studies in Management Sciences, Vol. 1: Logistics, Elsevier, Cambridge, MA (1975)

23.

Usuga Cadavid, J.P., Lamouri, S., Grabot, B., Pellerin, R., Fortin, A.: Machine learning applied in production planning and control: a state-of-the-art in the era of industry 4.0. J. Intell. Manuf. 31(6), 1531–1558 (2020). https://doi.org/10.1007/s10845-019-01531-7CrossRef

24.

Balzereit, K., & Niggemann, O.: Gradient-based Reconfiguration of Cyber-Physical Production Systems. In: 2021 4th IEEE International Conference on Industrial Cyber-Physical Systems (ICPS): Online, 10–13 May, 2021 (pp. 125–131). IEEE (2021)

25.

Graves, S.C.: A Review of Production Scheduling. Oper. Res. 29(4), 646–675 (1981). https://doi.org/10.1287/opre.29.4.646CrossRefMATH

26.

Kuhnle, A.: Adaptive Order Dispatching based on Reinforcement Learning - Application in a Complex Job Shop in the Semiconductor Industry. Dissertation, Karlsruher Institut für Technologie (KIT), Karlsruhe (2020)

27.

Waschneck, B., Reichstaller, A., Belzner, L., Altenmuller, T., Bauernhansl, T., Knapp, A., & Kyek, A.: Deep reinforcement learning for semiconductor production scheduling. In: 2018 29th Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC). IEEE. https://doi.org/10.1109/asmc.2018.8373191 (2018).

28.

Kritzinger, W., Karner, M., Traar, G., Henjes, J., Sihn, W.: Digital Twin in manufacturing: A categorical literature review and classification. IFAC-PapersOnLine 51(11), 1016–1022 (2018). https://doi.org/10.1016/j.ifacol.2018.08.474CrossRef

29.

Schuh, G., Anderl, R., Gausemeier, J., Ten Hompel, M., & Wahlster, W. (Eds.).: Industrie 4.0 Maturity Index: Die digitale Transformation von Unternehmen gestalten. Herbert Utz Verlag (2017)

30.

Julius Pfrommer, Jan-Felix Klein, Marco Wurster, Simon Rapp, Patric Grauberger, Gisela Lanza, Albert Albers, Sven Matthiesen, and Jürgen Beyerer: An Ontology for Remanufacturing Systems. Automatisierungstechnik 06/2022. https://doi.org/10.1515/auto-2021-0156 (2022)

31.

Tantik, E., & Anderl, R.: Integrated data model and structure for the asset administration shell in industrie 4.0. Procedia Cirp, 60, 86–91 (2017)

32.

Vorderer, M., Junker, S., Lechler, A., & Verl, A.: CESA 3 R: highly versatile plug-and-produce assembly system. In: 2016 IEEE International Conference on Automation Science and Engineering (CASE) (pp. 745–750). IEEE (2016)

33.

Stillig, J., & Parspour, N.: Advanced manufacturing based on the intelligent floor: An infrastructure platform for the convertible production in the factory of the future. In: 2020 IEEE 20th Mediterranean Electrotechnical Conference (MELECON) (pp. 248–253). IEEE (2020)

34.

Ewert, D., Jung, T., Tasci, T., Stiedl, T.: Assets2036 – Lightweight Implementation of the Asset Administration Shell Concept for Practical Use and Easy Adaptation. In: Weißgraeber, P., Heieck, F., Ackermann, C. (eds.) Advances in Automotive Production Technology – Theory and Application. A, pp. 153–161. Springer, Heidelberg (2021). https://doi.org/10.1007/978-3-662-62962-8_18CrossRef

Title: Improving Production System Flexibility and Changeability Through Software-Defined Manufacturing
Authors: S. Behrendt
M. Ungen
J. Fisel
K.-C. Hung
M.-C. May
U. Leberle
G. Lanza
Publisher: Springer International Publishing
Book: Production at the Leading Edge of Technology
Print ISBN: 978-3-031-18317-1

Electronic ISBN: 978-3-031-18318-8

Copyright Year: 2023
DOI: https://doi.org/10.1007/978-3-031-18318-8_70

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