Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-23T01:21:25.713Z Has data issue: false hasContentIssue false
  • English
  • Français

Methodology for Early Design Phase Cost and Performance Trade-Off Analysis of a New Variant in a Product Family

Published online by Cambridge University Press:  26 May 2022

M. Schaffers ,
E. Rosseel ,
S. Burggraeve ,
J. Pelfrene ,
K. Gadeyne  and
F. Petré
M. Schaffers
Affiliation:
Flanders Make, Belgium
E. Rosseel
Affiliation:
Flanders Make, Belgium
S. Burggraeve*
Affiliation:
Flanders Make, Belgium
J. Pelfrene
Affiliation:
Flanders Make, Belgium
K. Gadeyne
Affiliation:
Flanders Make, Belgium
F. Petré
Affiliation:
Flanders Make, Belgium
*
[email protected]

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.

Given the Industry 4.0 trend towards smaller lot sizes and large product families, there is a need to increase the design efficiency in terms of cost and lead time. Design decisions taken in the early or conceptual design phases are shown to have the greatest impact on the final product cost, however the choices and trade-offs are often made in an ad-hoc way. This paper presents a structured methodology for formalizing early stage product design knowledge, which is key for designing and evaluating new variants in a product family in the early stages of the design process.

Keywords

design knowledgeproduct familiesearly design phasecost-performance trade-offsknowledge formalisation
Type
Article
Information
Proceedings of the Design Society , Volume 2: DESIGN2022 , May 2022 , pp. 593 - 602
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

Asadi, N. , Jackson, M. and Fundin, A. (2016), “Drivers of Complexity in a Flexible Assembly System- A Case Study”, Procedia CIRP Vol. 41, CIRP Society, Ischia, pp. 189–194. 10.1016/j.procir.2015.12.082CrossRefGoogle Scholar
Benavides, B., Trinidad, P. and Ruiz-Cortés, A. (2005), “Automated Reasoning on Feature Models”, In: Pastor, O., Falcão e Cunha, J. (Eds.), Advanced Information Systems Engineering (Lecture Notes in Computer Science, vol. 3520), Springer Verlag, Berlin, Heidelberg, pp. 361–373. 10.1007/11431855_34Google Scholar
Bonev, M., Hvam, L., Clarkson, J. and Maier, A. (2015), “Formal computer-aided product family architecture design for mass customization”, Computers in Industry, Vol. 74, pp. 58–70. 10.1016/j.compind.2015.07.006CrossRefGoogle Scholar
Floridi, L. (2008), “The Method of Levels of Abstraction”, Minds and Machines, Vol. 18 No. 3, pp. 303–329. 10.1007/s11023-008-9113-7Google Scholar
ISA (2010), ANSI/ISA-95.00.01-2010: Enterprise-Control System Integration - Part 1: Models and Terminology, International Society of Automation, North Carolina.Google Scholar
Jiao, J., T.W. and Siddique, Z. (2007), “Product family design and platform-based product development: a state-of-the-art review.”, J. Intell Manuf, Vol. 18, pp. 5–29. 10.1007/s10845-007-0003-2Google Scholar
Robertson, D. and Ulrich, K. (1998), Planning for product platforms. [online] MIT Sloan Management Review. Available at https://sloanreview.mit.edu/article/planning-for-product-platforms/ (accessed 05.10.2021).Google Scholar
Simpson, T. W. (2004), “Product platform design and customization: Status and promise”, AI EDAM, Vol. 18 No. 1, pp. 3–20. 10.1017/S0890060404040028Google Scholar
Thomke, S. (2001), Enlighted Experimentation: The New Imperative for Innovation. [online] Harvard Business Review. Available at: https://hbr.org/2001/02/enlightened-experimentation-the-new-imperative-for-innovation (accessed 04.10.2021).Google Scholar
Windheim, M. (2020), “State of the Art in Product Family Design and Evaluation”, In: Gruen, Alexander (Ed.), Cooperative Decision-Making in Modular Product Family Design (Produktenentwicklung und Konstruktionstechnik Vol 17), , Springer Berlin Heidelberg, pp. 33–78. 10.1007/978-3-662-60715-2_3CrossRefGoogle Scholar
Zeng, F., Li, B., Zheng, P. and Xie, S.S.Q. (2014), “A modularized generic product model in support of product family modeling in One-of-a-Kind Production”, Proceedings of the 2014 IEEE International Conference on Mechatronics and Automation, IEEE, Tianjin, pp. 786–791. 10.1109/ICMA.2014.6885797Google Scholar