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Development Method for Enabling the Utilisation of a Sensory Function in a Central Component Based on Its Physical Properties

Published online by Cambridge University Press:  26 May 2022

B. Kraus ,
J. V. Schwind  and
E. Kirchner
B. Kraus*
Affiliation:
Technical University of Darmstadt, Germany
J. V. Schwind
Affiliation:
Technical University of Darmstadt, Germany
E. Kirchner
Affiliation:
Technical University of Darmstadt, Germany
*
[email protected]

Abstract

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In the context of condition monitoring and predictive maintenance, collecting accurate data from technical systems is an important corner stone of the advancing digitalization. For gathering precise data of the current state of a system, measurements from within the process can be utilised. To measure in process without disrupting the system is a challenge that can be tackled by using the physical properties of the components of the system. In this paper a method to systematically find such possible sensory utilizable components (SuC), based on their inherent physical effects is presented.

Keywords

effect cataloguedesign methodssensor developmentdesign researchmethodical design
Type
Article
Information
Proceedings of the Design Society , Volume 2: DESIGN2022 , May 2022 , pp. 1619 - 1628
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), 2022.

References

Albers, A., Burkardt, N. and Ohmer, M. (2004), “Principles for design on the abstract level of the contact & channel model”, paper presented at TCME, 13-17 April, Lausanne, Switzerland.Google Scholar
Blessing, L.T.M. and Chakrabarti, A. (2009), DRM, a design research methodology, Springer, Dordrecht, Heidelberg.Google Scholar
Ehrlenspiel, K. and Meerkamm, H. (2017), Integrierte Produktentwicklung, Carl Hanser Verlag GmbH & Co. KG.Google Scholar
Fleischer, J., Klee, B., Spohrer, A. and Merz, S. Metten, B. (2018), Leitfaden Sensorik für Industrie 4.0 - Wege zu kostengünstigen Sensorsystemen.Google Scholar
Gericke, K., Eckert, C., Campean, F., Clarkson, P.J., Flening, E., Isaksson, O., Kipouros, T., Kokkolaras, M., Köhler, C., Panarotto, M. and Wilmsen, M. (2020), “Supporting designers: moving from method menagerie to method ecosystem”, Design Science, Vol. 6.Google Scholar
Groche, P. and Brenneis, M. (2014), “Manufacturing and use of novel sensoric fasteners for monitoring forming processes”, Measurement, Vol. 53, pp. 136–144.Google Scholar
Großkurth, D. and Martin, G. (2019), “P2.14 Intelligenter Zahnriemen”, in AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf.Google Scholar
Harder, A., Gross, H.J., Vorwerk-Handing, G. and Kirchner, E. (2021), “Using effect catalogues for the design of sensing machine elements - method adn exemplary application”, Proceedings of the Design Society, Vol. 1, pp. 3359–3368.CrossRefGoogle Scholar
Harder, A., Hausmann, M., Kraus, B., Kirchner, E. and Hasse, A. (2022), “Sensory Utilizable Design Elements: Classifications, Applications and Challenges”, Applied Mechanics, Vol. 3 No. 1, pp. 160–173.Google Scholar
Janschek, K. (2010), Systementwurf mechatronischer Systeme: Methoden – Modelle – Konzepte, SpringerLink Bücher, Springer Berlin Heidelberg, Berlin, Heidelberg.Google Scholar
Jung, D. and DeSmidt, H. (2018), “A new hybrid observer based rotor imbalance vibration control via passive autobalancer and active bearing actuation”, Journal of Sound and Vibration, Vol. 415, pp. 1–24.Google Scholar
Kirchner, E. (2020), Werkzeuge und Methoden der Produktentwicklung, Springer Berlin Heidelberg, Berlin, Heidelberg.Google Scholar
Kirchner, E., Martin, G. and Vogel, S. (2018), “Sensor Integrating Machine Elements. Key to In-Situ Measurements in Mechanical engineering”, paper presented at Seminário Internacional de Alta Tecnologia, 04. 10. 2018, Piracicaba, SP, Brasil.Google Scholar
Kraus, B., Schmitt, F., Steffan, K.-E. and Kirchner, E. (2021), “A valve closing body as a central sensory-utilizable component”, Procedia CIRP, Vol. 100, pp. 109–114.Google Scholar
Le Masson, P., Weil, B. and Hatchuel, A. (2017), “Designing in an Innovative Design Regime—Introduction to C-K Design Theory”, in Le Masson, P., Weil, B. and Hatchuel, A. (Eds.), Design Theory, Springer International Publishing, Cham, pp. 125–185.CrossRefGoogle Scholar
Mahle GmbH (2013), Ventiltrieb: Systeme und Komponenten, Springer eBook Collection, Springer Vieweg, Wiesbaden.Google Scholar
Mathias, J. (2016), “Auf dem Weg zu robusten Lösungen: Modelle und Methoden zur Beherrschung von Unsicherheit in den frühen Phasen der Produktentwicklung”, Dissertation, pmd, TU Darmstadt, Darmstadt, 2016.Google Scholar
Matthiesen, S. (2021), “Gestaltung – Prozess und Methoden”, in Bender, B. and Gericke, K. (Eds.), Pahl/Beitz Konstruktionslehre, Vol. 22, Springer Berlin Heidelberg, Berlin, Heidelberg, pp. 397–465.Google Scholar
Pahl, G. and Beitz, W., Gericke, K. (2021), “Grundlagen technischer Systeme”, in Bender, B. and Gericke, K. (Eds.), Pahl/Beitz Konstruktionslehre, Springer Berlin Heidelberg, Berlin, Heidelberg, pp. 9–25.Google Scholar
Petko, M. and Uhl, T. (2004), “Smart sensor for operational load measurement”, Transactions of the Institute of Measurement and Control, Vol. 26 No. 2, pp. 99–117.CrossRefGoogle Scholar
Schirra, T., Martin, G. and Kirchner, E. (2021), “Design of and with sensing machine elements - using the example of a sensing rolling bearing”, Proceedings of the Design Society, Vol. 1, pp. 1063–1072.Google Scholar
Smart Engineering (2012), Springer Berlin Heidelberg, https://dx.doi.org/10.1007/978-3-642-29372-6.Google Scholar
Trent, H.M. (1955), “Isomorphisms between Oriented Linear Graphs and Lumped Physical Systems”, The Journal of the Acoustical Society of America, Vol. 27 No. 3, pp. 500–527.Google Scholar
Verein Deutscher Ingenieure (1997), VDI 2222: Methodisches Entwickeln von Lösungsprinzipien, Beuth Verlag GmbH.Google Scholar
Verein Deutscher Ingenieure (2019), VDI 2221 part 1: Design of technical products and systems - Model of product design, Beuth Verlag GmbH.Google Scholar
Verein Deutscher Ingenieure (2021), VDI/VDE 2206:2021: Entwicklung mechatronischer und cyber-physischer Systeme, Beuth Verlag GmbH.Google Scholar
Vogel, S. (2021), “Das Lastpfad und Knotenmodell. Eine Erweiterung des C&C²-Ansatzes zur Bewertung von Ersatzgrößen in der Produktentwicklung mechatronischer Systeme”, Dissertation, pmd, TU Darmstadt, Darmstadt, 2021.Google Scholar
Vorwerk-Handing, G. (2021), “Erfassung systemspezifischer Zustandsgrößen. Physikalische Effektkataloge zur systematischen Identifikation potentieller Messgrößen”, Dissertation, pmd, TU Darmstadt, Darmstadt, 2021.Google Scholar
Vorwerk-Handing, G., Gwosch, T., Schork, S., Kirchner, E. and Matthiesen, S. (2020), “Classification and examples of next generation machine elements”, Forschung im Ingenieurwesen, Vol. 84 No. 1, pp. 21–32.CrossRefGoogle Scholar
Welzbacher, P., Schulte, F., Neu, M., Koch, Y. and Kirchner, E. (2021), “An approach for the quantitative description of uncertainty to support robust design in sensing technology”, Design Science, Vol. 7.Google Scholar