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AN ADAPTED METHOD FOR DESIGN PROCESS CAPTURING TO MEET THE CHALLENGES OF DIGITAL PRODUCT DEVELOPMENT

Published online by Cambridge University Press:  27 July 2021

Benjamin Gerschütz*
Affiliation:
Friedrich-Alexander-Universität Erlangen-Nürnberg
Bettina Vanessa Martina Spießl
Affiliation:
Friedrich-Alexander-Universität Erlangen-Nürnberg
Schleich Benjamin
Affiliation:
Friedrich-Alexander-Universität Erlangen-Nürnberg
Sandro Wartzack
Affiliation:
Friedrich-Alexander-Universität Erlangen-Nürnberg
*
Gerschütz, Benjamin, Friedrich-Alexander-Universität Erlangen-Nürnberg, Engineering Design, Germany, [email protected]

Abstract

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In our modern, interconnected and globalized world, design is in motion, to adapt to new situations. But successful Design in Motion must be based on Processes in Motion. For a target-oriented adaptation of the processes to the new, challenging conditions, the as-is procedures must be captured and analysed. For this analysis, established capturing procedures from production or administration cannot be used due to some special features of design processes and workflows, which will be discussed in this contribution. To compensate for the weaknesses of existing methods, we propose an adapted method for holistic design process capturing. With the procedure, we want to enable an economic process analysis, which is crucial for small and medium-size companies in particular. To give an insight into the practical application of the method, we exemplarily analyse the process of a shaft construction and FEM-evaluation by two different employees. Based on this analysis and to verify the relevance of the presented approach, an evaluation with respect to the requirements is done.

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2021. Published by Cambridge University Press

References

VDI 2206: Design methodology for mechatronic systems (2004).Google Scholar
Becker, J., Probandt, W., and Vering, O. (2012), Grundsätze ordnungsmässiger Modellierung: Konzeption und Praxisbeispiel für ein effizientes Prozessmanagement, Springer Gabler. Berlin. https://doi.org/10.1007/978-3-642-30412-5.CrossRefGoogle Scholar
Best, E. and Weth, M. (2009), Geschäftsprozesse optimieren: Der Praxisleitfaden für erfolgreiche Reorganisation, Gabler Verlag/GWV Fachverlage GmbH, Wiesbaden. https://doi.org/10.1007/978-3-322-94581-5.CrossRefGoogle Scholar
Blessing, L.T.M. and Chakrabarti, A. (2009), DRM, a Design Research Methodology, Springer London, London. https://doi.org/10.1007/978-1-84882-587-1.CrossRefGoogle Scholar
Brenner, J. (2018), Lean Administration: Verschwendung in Büros erkennen, analysieren und beseitigen, Praxisreihe Qualitätswissen, Hanser, München. https://doi.org/10.3139/9783446455795.fm.CrossRefGoogle Scholar
Dumas, M., La Rosa, M., Mendling, J., and Reijers, H. A. (2018), Fundamentals of Business Process Management. 2nd ed., Springer, Berlin Heidelberg. https://doi.org/10.1007/978-3-662-56509-4.CrossRefGoogle Scholar
Dymora, P., Koryl, M., and Mazurek, M. (2019), “Process Discovery in Business Process Management Optimization”, Information, Vol. 10, p.270. https://doi.org/10.3390/info1009027.CrossRefGoogle Scholar
Grimm, F. and Gentemann, L. (2020), Digital Engineering - Agile Produktentwicklung in der deutschen Industrie, Bitkom Research, 2020.Google Scholar
Kitchin, R. and McArdle, G. (2016), “What makes Big Data, Big Data? Exploring the ontological characteristics of 26 datasets”. Big Data & Society, Vol. 3. https://doi.org/10.1177/2F2053951716631130.CrossRefGoogle Scholar
Koubarakis, M. and Plexousakis, D. (1999), “Business Process Modelling and Design - A Formal Model and Methodology”, BT Technology Journal, Bd, 17, pp. 2335. https://doi.org/10.1023/A:1009686723414.CrossRefGoogle Scholar
Lewin, M., Busert, T., El Sakka, F., Voigtländer, S., and Fay, A. (2019) “Leitfaden Mit Wertstromdesign Industrie 4.0 gestalten”.Google Scholar
Leyh, C., Bley, K., Seek, S. (2017) “Elicitation of Processes in Business Process Management in the Era of Digitization – The Same Techniques as Decades Ago?”, ERP Future 2016, Hagenberg, Austria. https://doi.org/10.1007/978-3-319-58801-8_4Google Scholar
Mehlstäubl, J., Atzberger, A., and Paetzold, K. (2020), “General Approach to support Modelling of Data and Information Flows in Product Development”, NordDESIGN, Lyngby, Denmark, The Design Society. https://doi.org/10.35199/NORDDESIGN2020.47Google Scholar
Meuth, T., Metternich, J., and Abele, E. (2017), “Value stream mapping 4.0: Holistic examination of value stream and information logistics in production”, CIPR Annals, Vol. 66, No. 1, pp. 413446. https://doi.org/10.1016/j.cirp.2017.04.005.Google Scholar
Pahl, G., Beitz, W., Feldhusen, J., and Grote, K.-H. (2007), Engineering Design: A Systematic Approach, Springer, Berlin. http://doi.org/10.1007/978-1-4471-3581-4.CrossRefGoogle Scholar
Pöhler, L., Schuir, J., Lübbers, S., and Teuteberg, F. (2020), “Enabling Collaborative Business Process Elicitation in Virtual Environments”, BMSD 2020, Berlin, Germany, 6th - 8th July 2020, Springer, Cham, pp. 375385. https://doi.org/10.1007/978-3-030-52306-0_27.CrossRefGoogle Scholar
Roelofsen, J.M.K. and Lindemann, U. (2010), “An Approach Towards Planning Development Processes According to the Design Situation”, In: Heisig, P., Clarkson, P. J., Vajna, S. (Eds.), Modelling and Management of Engineering Processes, Springer, London. https://doi.org/10.1007/978-1-84996-199-8_4.Google Scholar
Sharp, A. and McDermott, P. (2009), Workflow modeling tools for process improvement and applications development, Artech House, Boston.Google Scholar
Vajna, S., Weber, C., Zeman, K., Hehenberger, P., Gerhard, D., and Wartzack, S. (2018), CAx für Ingenieure: eine praxisbezogene Einführung. 3. Edition. Springer, Berlin, Germany. https://doi.org/10.1007/978-3-540-36039-1.CrossRefGoogle Scholar
van der Aalst, W. M. P., Rubin, V., Verbeek, H. M. W., van Dongen, B. F., Kindler, E., and Günther, C. W. (2010), “Process mining: a two-step approach to balance between underfitting and overfitting”, Software & Systems Modeling, Bd. 9, No. 1, pp. 87111. https://doi.org/10.1007/s10270-008-0106-z.CrossRefGoogle Scholar
van der Aalst, W. (2016), Process mining: data science in action, 2nd edition, Springer, New York, NY. https://doi.org/10.1007/978-3-662-49851-4.CrossRefGoogle Scholar
Wickel, M., Schenkl, S. A., Schmidt, D. M., Hense, J. U., Mandl, H., and Maurer, M. (2013), “Knowledge structure maps based on multiple domain matrices”, InImpact: The Journal of Innovation Impact, Bd. 5, pp. 516.Google Scholar