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Management of rule-based product-portfolios with high variance: a systematic literature review

Published online by Cambridge University Press:  16 May 2024

Thorsten Schmidt*
Affiliation:
Helmut Schmidt University Hamburg, Germany
Frank Mantwill
Affiliation:
Helmut Schmidt University Hamburg, Germany

Abstract

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This paper conducts a systematic literature review about the management of rule-based product-portfolios with high variance. This type of portfolio is particularly distinctive in the chosen use case of the German automotive industry since it satisfies the requirements of mass customization and modularization. However, the research field of variant- and complexity management is manifold and multidimensional. This paper systematically searches the databases Scopus and Web of Science using the PRISMA method and briefly summarizes the main contributions and comparing them by elaborated topics.

Type
Design Methods and Tools
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), 2024.

References

Albers, A., Haug, F., Fahl, J., Hirschter, T., Reinemann, J. and Rapp, S. (2018), "Customer-oriented product development: supporting the development of the complete vehicle through the systematic use of engineering generations", Proceedings of 4th IEEE International Symposium on Systems Engineering, ISSE 2018, Rom, https://doi.org/10.1109/SysEng.2018.8544391CrossRefGoogle Scholar
Andersson, H., Carlsson, M. and Ölvander, J. (2011), "Towards configuration support for collaborative simulator development: A product line approach in model-based systems engineering", Proceedings of the 2011 20th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises, WETICE 2011, pp. 185-192, https://doi.org/10.1109/WETICE.2011.74CrossRefGoogle Scholar
Bittner, M., Reiser, M.-O. and Weber, M. (2010), "A case study on tool-supported multi-level requirements management in complex product families", Lecture Notes in Computer Science Volume 6182 LNCS, pp. 173 - 187, 2010 16th International Working Conference on Requirements Engineering: Foundation for Software Quality, REFSQ 2010, 30 June 2010 through 2 July 2010, https://doi.org/10.1007/978-3-642-14192-8_17CrossRefGoogle Scholar
Bracht, U. and Holtze, P. (1999), "Data mining for better parts-requirement forecasting. New approaches to planning with wide variation in series production", ZWF Zeitschrift für Wirtschaftlichen Fabrikbetrieb, Carl Hanser Verlag, Volume 94, Issue 4, pp. 119 - 122, March 1999, https://doi.org/10.1515/zwf-1999-0044CrossRefGoogle Scholar
Braun, F., Kreimeyer, M., Kopal, B. and Paetzold, K. (2017), "Challenges in the validation of the variant description of complex products" DFX 2017: Proceedings of the 28th Symposium Design for X, pp. 61 - 73, 2017, 28th Symposium Design for X, DFX 2017, Bamberg, 4 October 2017 through 5 October 2017, ISBN: 978-3-946094-20-3-6Google Scholar
Braun, F., Kreimeyer, M. and Paetzold, K. (2018), "Procedural model to ensure consistency and validity of complex, variant-oriented product portfolios", Proceedings of NordDesign: Design in the Era of Digitalization, NordDesign 2018, 13th Biennial Norddesign Conference, NordDesign 2018, Linkoping, 14 August 2018 through 17 August 2018, ISBN: 978-917685185-2Google Scholar
Franklin, W. E. and Hunt, R. G. (1998), "Can a Universal Screening Methodology be Devised for LCAs of Complex Products?", SAE Technical Papers 980476, SAE International Congress and Exposition, 1998, https://doi.org/10.4271/980476CrossRefGoogle Scholar
Franze, H.A. and Neumann, U. (1997), "Design for Environmental Compatibility of Automobiles - New Life-Cycle Management Tools in the BMW Product Development Process", SAE Technical Papers 971192, SAE International, https://doi.org/10.4271/971192CrossRefGoogle Scholar
Frischen, C., Marbach, A., Tichla, F. and Mantwill, F. (2019), "Consistent controlling of variants with the aid of the rule-based complex bill of materials", Proceedings of the 30th Symposium Design for X, DFX 2019, pp. 13 - 24, 30th Symposium Design for X, DFX 2019, Jesteburg, 18 September 2019 through 19 September 2019, https://doi.org/10.35199/dfx2019.2CrossRefGoogle Scholar
Greisel, M., Kissel, M., Spinola, B. and Kreimeyer, M. (2013), "Design for adaptability in multi-variant product families", Proceedings of the International Conference on Engineering Design, ICED, Volume 4, DS75-04, pp. 179 - 188, 2013, 19th International Conference on Engineering Design, ICED 2013, 19 August 2013 through 22 August 2013, ISBN: 978-1-904670-47-6, ISSN: 2220-4334Google Scholar
Herlyn, Wilmjakob (1990), "Zur Problematik der Abbildung variantenreicher Erzeugnisse in der Automobilindustrie", VDI Verlag, Düsseldorf, 1990Google Scholar
Herlyn, Wilmjakob (2005), "Individual owner's manual for serial products with many variants", ZWF Zeitschrift für Wirtschaftlichen Fabrikbetrieb, Carl Hanser Verlag, Volume 100, Issue 5, pp. 291 - 298, May 2005, https://doi.org/10.3139/104.100899CrossRefGoogle Scholar
Johansson, P. E. C., Mattsson, S., Moestam, L. and Fast-Berglund, A. (2016), "Multi-variant Truck Production - Product Variety and its Impact on Production Quality in Manual Assembly", Procedia CIRP, Volume 54, pp. 245 - 250, 2016 6th CIRP Conference on Learning Factories, CLF 2016, Gjovik, 29 June 2016 through 30 June 2016, https://doi.org/10.1016/j.procir.2016.05.062CrossRefGoogle Scholar
Kobayashi, O., Teulon, H., Osset, P. and Morita, Y. (1998), "Life cycle analysis of a complex product, application of ISO 14040 to a complete car", SAE Technical Papers, SAE International, 1998, Total Life Cycle Conference and Exposition, 1 December 1998 through 3 December 1998, https://doi.org/10.4271/982187CrossRefGoogle Scholar
Küchlin, W. and Sinz, C. (2000), "Proving consistency assertions for automotive product data management", Journal of Automated Reasoning, Kluwer Academic Publishers, Volume 24, Issue 1-2, pp. 145 - 163, Feb 2000, https://doi.org/10.1023/a:1006370506164Google Scholar
Li, Y., Ni, Y., Zhang, N. and Liu, Z. (2021), "Modularization for the complex product considering the design change requirements", Research in Engineering Design, Springer Science and Business Media Deutschland GmbH, Volume 32, Issue 4, pp. 507 - 522, October 2021, https://doi.org/10.1007/s00163-021-00369-6CrossRefGoogle Scholar
Mehlstäubl, J., Pfeiffer, C., Kraul, R., Braun, F. and Paetzold-Byhain, K. (2023), "Methodical approach to cluster configurations of product variants of complex product portfolios", Proceedings of the Design Society, Volume 3, pp. 2645 - 2654, 2023, 24th International Conference on Engineering Design, ICED 2023, Bordeaux, 24 July 2023 through 28 July 2023, https://doi.org/10.1017/pds.2023.265CrossRefGoogle Scholar
Page, M.J., Moher, D., Bossuyt, P.M., Boutron, I., Hoffmann, T.C., Mulrow, C.D. and Shamseer, L. (2021), “PRISMA 2020 explanation and elaboration: Updated guidance and exemplars for reporting systematic reviews”, British Medical Journal, BMJ Publishing Group, Vol. 372. https://doi.org/10.1136/bmj.n160Google Scholar
Persson, M. (2004), "Managing the Modularization of Complex Products", Doktorsavhandlingar vid Chalmers Tekniska Hogskola, Issue 2077, 2004, ISBN: 91-7291-395-9Google Scholar
Persson, M. and Ahlstrom, Pär (2006), "Managerial issues in modularising complex products", Technovation, Volume 26, Issue 11, pp. 1201 - 1209, November 2006, https://doi.org/10.1016/j.technovation.2005.09.020CrossRefGoogle Scholar
Raza, M. B. and Harrison, R. (2011), "Ontological knowledge-based system for product, process and resource relationships in automotive industry", CEUR Workshop Proceedings, Volume 748, pp. 23 - 36, 2011, 1st International Workshop on Ontology and Semantic Web for Manufacturing 2011, OSEMA 2011 - Co-located with the 8th Extended Semantic Web Conference, ESWC 2011, 29 May 2011 through 29 May 2011, ISSN: 16130073, https://api.semanticscholar.org/CorpusID:16247915Google Scholar
Sinz, C. (1997), Baubarkeitsprüfung von Kraftfahrzeugen durch automatisches Beweisen [Master Thesis], Wilhelm-Schickard-Institut für Informatik, Arbeitsbereich Symbolisches Rechnen, Eberhard-Karls-Universität Tübingen, Tübingen, Germany, 1997Google Scholar
Stich, C. (2007), "Produktionsplanung in der Automobilindustrie: Optimierung des Ressourceneinsatzes im Serienanlauf", Wissenschaftsverlag, Köln, 2007, https://doi.org/10.1007/978-3-658-26352-2CrossRefGoogle Scholar
Thiel, S., Babar, M. A., Botterweck, G. and O'Brien, L. (2008), "Software product lines in automotive systems engineering", SAE Technical Papers, SAE International, 2008, https://doi.org/10.4271/2008-01-1449CrossRefGoogle Scholar
Hommes, Van Eikema, D, Q.. (2009), "Comparison and Application of Metrics That Define the Components Modularity in Complex Products", Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC 2008, Volume 4, pp. 287 - 296, 2009, 3 August 2008 through 6 August 2008, ISBN: 978-079184325-3, 978-079184328-4, https://doi.org/10.1115/DETC2008-49140CrossRefGoogle Scholar
VDI (2019), VDI-Standard VDI 2221 - Part 1 2019, Design of technical products and systems, Berlin, Beuth Verlag, 2019Google Scholar
Yamamura, C. L. K., Santana, J. C. C., Masiero, B. S., Quintanilha, J. A. and Berssaneti, F. T. (2022), "Forecasting New Product Demand Using Domain Knowledge and Machine Learning: A proposed method uses machine learning and an expert's domain knowledge to enhance the accuracy of new product predictions", Research Technology Management, Volume 65, Issue 4, pp. 27 - 36, 2022, https://doi.org/10.1080/08956308.2022.2062553Google Scholar