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CONFIGURING CUSTOMIZED PRODUCTS WITH DESIGN OPTIMIZATION AND VALUE-DRIVEN DESIGN

Published online by Cambridge University Press:  27 July 2021

Olle Vidner ,
Camilla Wehlin ,
Johan A Persson  and
Johan Ölvander
Olle Vidner*
Affiliation:
Linköping University
Camilla Wehlin
Affiliation:
Linköping University
Johan A Persson
Affiliation:
Linköping University
Johan Ölvander
Affiliation:
Linköping University
*
Vidner, Olle, Linköping University, Division of Product Realisation, Sweden, olle.vidner@liu.se

Abstract

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In order to efficiently design and deliver customized products, it is crucial that the process of translating customer needs to engineering characteristics and into unique products is smooth and without any misinterpretations. The paper proposes a method that combines design optimization with value-driven design to support and automate configuration of customized products. The proposed framework is applied to a case example with spiral staircases, a product that is uniquely configured for each customer from a set of both standard and customized components; a process that is complex, iterative and error-prone. In the case example, the optimization and value-driven design models are used to automate and speed-up the process of delivering quotations and design proposals that could be judged based on both engineering characteristics as well as their added value, thereby increasing the knowledge at the sales stage. Finally, a multi-objective optimization algorithm is employed to generate a set of Pareto-optimal solutions that contain four clusters of solutions that dominate the baseline design. Hence the decision-maker is given a set of optimal solutions to choose from when balancing different economical and technical characteristics.

Keywords

OptimisationProduct architectureDigital / Digitised engineering value chainsStaircases
Type
Article
Information
Proceedings of the Design Society , Volume 1: ICED21 , August 2021 , pp. 741 - 750
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

Amadori, K. et al. (2012). “Flexible and Robust CAD Models for Design Automation”. Advanced Engineering Informatics 26.2, pp. 180–195. DOI: 10/f228fq.CrossRefGoogle Scholar
Castagne, S., Curran, R., and Collopy, P. D. (2009). “Implementation of Value-Driven Optimisation for the Design of Aircraft Fuselage Panels”. International Journal of Production Economics 117.2, pp. 381–388. DOI: 10/dsqw6n.CrossRefGoogle Scholar
Collopy, P. D. (2012). “A Research Agenda for the Coming Renaissance in Systems Engineering”. 50th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition. Nashville, Tennessee: American Institute of Aeronautics and Astronautics. DOI: 10/gjsffd.Google Scholar
Collopy, P. D. and Hollingsworth, P. M. (2011). “Value-Driven Design”. Journal of Aircraft 48.3, pp. 749–759. DOI: 10/dmwprm.CrossRefGoogle Scholar
Deb, K. et al. (2002). “A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II”. IEEE Transactions on Evolutionary Computation 6.2, pp. 182–197. DOI: 10/bnw2vv.CrossRefGoogle Scholar
Forza, C. and Salvador, F. (2002). “Managing for Variety in the Order Acquisition and Fulfilment Process: The Contribution of Product Configuration Systems”. International Journal of Production Economics 76.1, pp. 87–98. DOI: 10/b42trp.CrossRefGoogle Scholar
Gray, J. S. et al. (2019). “OpenMDAO: An Open-Source Framework for Multidisciplinary Design, Analysis, and Optimization”. Structural and Multidisciplinary Optimization 59.4, pp. 1075–1104. DOI: 10/gfwtcb.CrossRefGoogle Scholar
Hoyer, S. and Hamman, J. J. (2017). “Xarray: N-D Labeled Arrays and Datasets in Python”. Journal of Open Research Software 5, p. 10. DOI: 10/gdqdmw.CrossRefGoogle Scholar
Hvam, L., Haug, A., et al. (2013). “Observed Benefits from Product Configuration Systems”. International Journal of Industrial Engineering: Theory, Applications and Practice 20.5-6, pp. 1–6.Google Scholar
Hvam, L., Mortensen, N. H., and Riis, J. (2008). Product Customization. Berlin: Springer.Google Scholar
Hwang, C.-L., Paidy, S., et al. (1980). “Mathematical Programming with Multiple Objectives: A Tutorial”. Computers & Operations Research 7.1-2, pp. 5–31. DOI: 10/bw8cvv.CrossRefGoogle Scholar
Hwang, C.-L. and Yoon, K. (1981). Multiple Attribute Decision Making. Red. by Beckmann, M. and Künzi, H. P.. Vol. 186. Lecture Notes in Economics and Mathematical Systems. Berlin, Heidelberg: Springer Berlin Heidelberg. DOI: 10/f8rt.Google Scholar
Krus, P. (2000). “Post Optimal System Analysis Using Aggregated Design Impact Matrix”. ASME International Design Engineering Technical Conference Computers and Information in Engineering Conference. American Society of Mechanical Engineers.CrossRefGoogle Scholar
Lambe, A. B. and Martins, J. R. R. A. (2012). “Extensions to the Design Structure Matrix for the Description of Multidisciplinary Design, Analysis, and Optimization Processes”. Structural and Multidisciplinary Optimization 46.2, pp. 273–284. DOI: 10/fzg48s.CrossRefGoogle Scholar
Lee, B. D. and Paredis, C. J. (2014). “A Conceptual Framework for Value-Driven Design and Systems Engineering”. Procedia CIRP 21, pp. 10–17. DOI: 10/gjgn8n.CrossRefGoogle Scholar
Martínez-Morales, J. D., Pineda-Rico, U., and Stevens-Navarro, E. (2010). “Performance Comparison between MADM Algorithms for Vertical Handoff in 4G Networks”. 2010 7th International Conference on Electrical Engineering Computing Science and Automatic Control, pp. 309–314. DOI: 10/b8gx99.CrossRefGoogle Scholar
Piller, F. T. (2004). “Mass Customization: Reflections on the State of the Concept”. International Journal of Flexible Manufacturing Systems 16.4, pp. 313–334. DOI: 10/cphjxw.CrossRefGoogle Scholar
Poot, L. P. et al. (2020). “Integrating Sales and Design: Applying CAD Configurators in the Product Development Process”. Proceedings of the Design Society: DESIGN Conference 1, pp. 345–354. DOI: 10/gjsffr.CrossRefGoogle Scholar
Price, M. et al. (2012). “A Novel Method to Enable Trade-Offs across the Whole Product Life of an Aircraft Using Value Driven Design”. Journal of Aerospace Operations 1.4, pp. 359–375. DOI: 10/gjsffq.CrossRefGoogle Scholar
Simpson, T. W. and Martins, J. R. R. A. (2011). “Multidisciplinary Design Optimization for Complex Engineered Systems: Report From a National Science Foundation Workshop”. Journal of Mechanical Design 133 10, pp. 101002-1–101002-10. DOI: 10/b2s9br.CrossRefGoogle Scholar
Tseng, M. M. and Piller, F. T., eds. (2003). The Customer Centric Enterprise: Advances in Mass Customization and Personalizaton. Berlin; New York: Springer. 535 p.CrossRefGoogle Scholar
Ullman, D. G. (2010). The Mechanical Design Process. 4th ed. McGraw-Hill Series in Mechanical Engineering. Boston: McGraw-Hill Higher Education. 433 pp.Google Scholar
Verhagen, W. J. C., Stjepandíc, J., and Wognum, N., eds. (2015). Concurrent Engineering in the 21st Century: Foundations, Developments and Challenges. 1st ed. Cham: Springer. 839 pp. DOI: 10/f8rv.Google Scholar
Vidner, O. (2020a). OpenMDAO-NSGA: NSGA-II and NSGA-III Implementations for OpenMDAO. Version v0.1. Zenodo. DOI: 10.5281/ZENODO.4279483.CrossRefGoogle Scholar
Vidner, O. (2020b). Scop: An Opinionated, Self-Contained Data Format and Post-Optimization Toolchain. Version v0.3. Zenodo. DOI: 10.5281/ZENODO.4263728.CrossRefGoogle Scholar
Wang, X. and Triantaphyllou, E. (2008). “Ranking Irregularities When Evaluating Alternatives by Using Some ELECTRE Methods”. Omega. Special Issue Section: Papers Presented at the INFORMS Conference, Atlanta, 2003 36.1, pp. 45–63. DOI: 10/fgjh9s.CrossRefGoogle Scholar
Weland, AB (2016). Product Manual Edition 6.Google Scholar