Hostname: page-component-8448b6f56d-mp689 Total loading time: 0 Render date: 2024-04-19T16:37:47.775Z Has data issue: false hasContentIssue false
  • English
  • Français

CRITERIA FOR SELECTING DESIGN PROCESS MODELLING APPROACHES

Published online by Cambridge University Press:  27 July 2021

Jakob Trauer ,
Ferdinand Wöhr ,
Claudia Eckert ,
Udo Kannengiesser ,
Sjoerd Knippenberg ,
Olga Sankowski  and
Markus Zimmermann
Jakob Trauer*
Affiliation:
Technical University of Munich
Ferdinand Wöhr
Affiliation:
Technical University of Munich BMW Group
Claudia Eckert
Affiliation:
The Open University
Udo Kannengiesser
Affiliation:
Johannes Kepler University
Sjoerd Knippenberg
Affiliation:
Eindhoven University of Technology
Olga Sankowski
Affiliation:
Hamburg University of Technology
Markus Zimmermann
Affiliation:
Technical University of Munich
*
Trauer, Jakob, Technical University of Munich, Laboratory for Product Development and Lightweight Structures, Germany, jakob.trauer@tum.de

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

Process models are among the principal artefacts used for managing design projects. However, the selection of effective modelling approaches can be difficult for design project managers, given that a plethora of tools exists for various modelling purposes. In addition to date no systematic approach for the assessment and selection of process modelling approaches is available to practitioners. This paper presents the development of criteria for benchmarking and selecting different process modelling tools. The results are based on three elements. (1) In a four-hour workshop undertaken by the Design Process SIG of the Design Society, bringing together around 20 international researchers and practitioners in design process modelling, an initial set of 58 criteria were brainstormed and consolidated during the workshop and in follow-up meetings. (2) The consolidated criteria were then compared with literature. The finalised criteria list was then validated by external experts in industry (3). The resulting list of 12 criteria provides a sound basis for practitioners to support a systematic selection of process modelling approaches. Further, it lays the foundation of a benchmarking tool, which is subject to future work.

Keywords

CriteriaDesign processProcess modellingDecision makingBenchmarking
Type
Article
Information
Proceedings of the Design Society , Volume 1: ICED21 , August 2021 , pp. 791 - 800
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

Aguilar-Savén, Ruth Sara (2004): Business process modelling: Review and framework. In International Journal of Production Economics 90 (2), pp. 129–149. http://doi.org/10.1016/S0925-5273(03)00102-6CrossRefGoogle Scholar
Browning, Tyson R. (2018): Building models of product development processes: An integrative approach to managing organizational knowledge. In Syst Eng 21 (1), pp. 70–87. http://doi.org/10.1002/sys.21421CrossRefGoogle Scholar
Browning, Tyson R.; Ramasesh, Ranga V. (2007): A Survey of Activity Network-Based Process Models for Managing Product Development Projects. In Production and Operations Management 16 (2), pp. 217–240. http://doi.org/10.1111/j.1937-5956.2007.tb00177.xCrossRefGoogle Scholar
Cameron, I. T.; Ingram, G. D. (2008): A survey of industrial process modelling across the product and process lifecycle. In Computers & Chemical Engineering 32 (3), pp. 420–438. http://doi.org/10.1016/j.compchemeng.2007.02.015CrossRefGoogle Scholar
Checkland, Peter (1999): Soft systems methodology. A 30-year retrospective. Systems thinking, systems practice. Peter Checkland. Chichester: Wiley.Google Scholar
Daalhuizen, Jaap; Badke-Schaub, Petra (2011): The use of methods by advanced beginner and and expert industrial designers in non-routine situations: a quasi-experiment. In International Journal of Product Development 15 (1-3), pp. 54–70. http://doi.org/10.1504/IJPD.2011.043661CrossRefGoogle Scholar
Eckert, Claudia M.; Clarkson, P. John (2010): Planning development processes for complex products. In Res Eng Design 21 (3), pp. 153–171. http://doi.org/10.1007/s00163-009-0079-0CrossRefGoogle Scholar
Eckert, Claudia M.; Wynn, David C.; Maier, Jakob F.; Albers, Albert; Bursac, Nikola; Chen, Xin, Hilario, L. et al. (2017): On the integration of product and process models in engineering design. In Des. Sci. 3, p. 137. https://doi.org/10.1017/dsj.2017.2CrossRefGoogle Scholar
Eisenmann, M.; Matthiesen, S. (2020): Identifying reasons for a lack of method application in engineering design practice – an interview study. In: Proceedings of the Design Society: DESIGN Conference, vol. 1, pp. 2495–2504. https://doi.org/10.1017/dsd.2020.261CrossRefGoogle Scholar
Eppinger, Steven D.; Browning, Tyson R. (2019): Design Structure Matrix Methods and Applications. Cambridge: The MIT Press.Google Scholar
Fleischmann, Albert; Schmidt, Werner; Stary, Christian; Obermeier, Stefan; Börger, Egon (2012): Subject-Oriented Business Process Management. Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-642-32392-8CrossRefGoogle Scholar
Gericke, K.; Eckert, C. M.; Wynn, D. (2016a): Towards a framework of choices made during the lifecycles of process models. In DS 84: Proceedings of the DESIGN 2016 14th International Design Conference, pp. 1275–1284.Google Scholar
Gericke, Kilian; Kramer, Julia; Roshuni, Celeste (2016b): An exploratory study of the discovery and selection of design methods in practice. In Journal of Mechanical Design 138 (10).10.1115/1.4034088CrossRefGoogle Scholar
Giaglis, George M. (2001): A Taxonomy of Business Process Modeling and Information Systems Modeling Techniques. In International Journal of Flexible Manufacturing Systems 13 (2), pp. 209–228. http://doi.org/10.1023/A:1011139719773CrossRefGoogle Scholar
Green, T.R.G.; Petre, M. (1996): Usability Analysis of Visual Programming Environments: A ‘Cognitive Dimensions’ Framework. In Journal of Visual Languages & Computing 7 (2), pp. 131–174. http://doi.org/10.1006/jvlc.1996.0009CrossRefGoogle Scholar
Helten, Katharina; Eckert, Claudia M.; Gericke, Kilian; Vermaas, Pieter (2021): Concept for a Persona Driven Recommendation Tool for Process Modelling Approaches. In Review. In: Proceedings of the 23rd International Conference on Engineering Design (ICED21). Gothenburg, Sweden, August 16-20, 2021. The Design Society: Cambridge University Press.Google Scholar
Standard ISO/IEC 19510:2013, 11/19/2020: Information technology - Object Management Group Business Process Model and Notation. Available online at https://www.iso.org/standard/62652.html, checked on 03/18/2021.Google Scholar
Kaschek, Roland; Pavlov, Roman; Shekhovtsov, Vladimir A.; Zlatkin, Sergiy (2006): Towards selecting among business process modeling methodologies. In 1617–5468. Available online at https://dl.gi.de/handle/20.500.12116/24153.Google Scholar
Krueger, Norris F.; Reilly, Michael D.; Carsrud, Alan L. (2000): Competing models of entrepreneurial intentions. In Journal of Business Venturing 15 (5-6), pp. 411–432. http://doi.org/10.1016/S0883-9026(98)00033-0CrossRefGoogle Scholar
Liu, Yan; Eckert, Claudia M.; Earl, Chris (2020): Assessing Suppliers for Complex Products From the Perspective of Power. In IEEE Trans. Eng. Manage., pp. 1–17. http://doi.org/10.1109/TEM.2020.2988056CrossRefGoogle Scholar
Luo, Wenhong; Alex Tung, Y. (1999): A framework for selecting business process modeling methods. In Industr Mngmnt & Data Systems 99 (7), pp. 312–319. http://doi.org/10.1108/02635579910262535CrossRefGoogle Scholar
Ouertani, M. Z.; Grebici, K.; Gzara, L.; Blanco, E.; Rieu, D. (2007): DEPNET: A Methodology for Identifying and Qualifying Dependencies Between Engineering Data. In Krause, Frank-Lothar (Ed.): The Future of Product Development. Proceedings of the 17th CIRP Design Conference. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, pp. 319–330. https://doi.org/10.1007/978-3-540-69820-3_32Google Scholar
Piccolo, Sebastiano A.; Trauer, Jakob; Wilberg, Julian; Maier, Anja M. (2018): Understanding task execution time in relation to the multilayer project structure: empirical evidence. In: DS 96: The 20th International DSM Conference. 20th International Dependency and Structure Modelling Conference (DSM 2018), pp. 129–138.Google Scholar
Prat, Nicolas; Madnick, Stuart (2008): Measuring Data Believability: A Provenance Approach. In: Proceedings of the 41st Annual Hawaii International Conference on System Sciences (HICSS 2008). 2008 41st Annual Hawaii International Conference on System Sciences. Waikoloa, HI, 07.01.2008 - 10.01.2008: IEEE, p. 393. https://doi.org/10.1109/HICSS.2008.243CrossRefGoogle Scholar
Recker, Jan; Mendling, Jan (2016): The State of the Art of Business Process Management Research as Published in the BPM Conference. In Bus Inf Syst Eng 58 (1), pp. 55–72. http://doi.org/10.1007/s12599-015-0411-3CrossRefGoogle Scholar
Saaty, Thomas L. (1990): How to make a decision: The analytic hierarchy process. In European Journal of Operational Research 48 (1), pp. 9–26. http://doi.org/10.1016/0377-2217(90)90057-ICrossRefGoogle Scholar
Sage, Andrew P.; Lynch, Charles L. (1998): Systems integration and architecting: An overview of principles, practices, and perspectives. In Syst Eng 1 (3), pp. 176–227. http://doi.org/10.1002/(SICI)1520-6858(1998)1:3<176AID-SYS3>3.0.CO;2-L3.0.CO;2-L>CrossRefGoogle Scholar
Stacey, Martin; Eckert, Claudia; Hillerbrand, Rafaela (2020): Process models: plans, predictions, proclamations or prophecies? In Res Eng Design 31 (1), pp. 83–102. http://doi.org/10.1007/s00163-019-00322-8CrossRefGoogle Scholar
Stapenhurst, Tim (2009): The Benchmarking book. A how-to-guide to best practice for managers and practitioners. Amsterdam: Elsevier. Available online at http://site.ebrary.com/lib/alltitles/docDetail.action?docID=10294740.Google Scholar
Vanderfeesten, Irene; Reijers, Hajo A.; Mendling, Jan; van der Aalst, Wil M. P.; Cardoso, Jorge (2008): On a Quest for Good Process Models: The Cross-Connectivity Metric. In Bellahsène, Zohra, Léonard, Michel (Eds.): Advanced Information Systems Engineering. 20th International Conference, CAiSE 2008 Montpellier, France, June 16-20, 2008 Proceedings. Berlin, Heidelberg, 2008. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg (Lecture Notes in Computer Science, 5074), pp. 480–494. https://doi.org/10.1007/978-3-540-69534-9_36Google Scholar
Wynn, David C.; Clarkson, P. John (2018): Process models in design and development. In Res Eng Design 29 (2), pp. 161–202. http://doi.org/10.1007/s00163-017-0262-7CrossRefGoogle Scholar
Wynn, David C.; Eckert, Claudia M.; Clarkson, P. John (2006): Applied Signposting: A Modeling Framework to Support Design Process Improvement. In: Volume 4a: 18th International Conference on Design Theory and Methodology. ASME 2006 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Philadelphia, Pennsylvania, USA, September 10–13, 2006: ASME, pp. 553–562. https://doi.org/10.1115/DETC2006-99402CrossRefGoogle Scholar