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Use of Margin to Absorb Variation in Design Specifications: An Analysis Using the Margin Value Method

Published online by Cambridge University Press:  26 May 2022

A. Brahma ,
D. C. Wynn  and
O. Isaksson
A. Brahma*
Affiliation:
Chalmers University of Technology, Sweden
D. C. Wynn
Affiliation:
The University of Auckland, New Zealand
O. Isaksson
Affiliation:
Chalmers University of Technology, Sweden
*
[email protected]

Abstract

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Predicting the impact of changes in a design can be challenging, especially for complex designs. Margins are often built into the designs which can absorb the knock-on effect of such changes, erroneously allocating which can however, lead to propagation. A method for localising and sizing margins in an incremental design context is the Margin Value Method. This paper adapts MVM in the context of uncertainty in input specifications. It discusses possible ways to allocate them in a design such that undesirable effects of margins are minimised while preventing change propagation.

Keywords

design marginrobust designengineering changedesign optimisation
Type
Article
Information
Proceedings of the Design Society , Volume 2: DESIGN2022 , May 2022 , pp. 323 - 332
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

Ahmad, N., Wynn, D.C. and Clarkson, P.J. (2013), “Change impact on a product and its redesign process: a tool for knowledge capture and reuse”, Research in Engineering Design, Springer, Vol. 24 No. 3, pp. 219–244. 10.1007/s00163-012-0139-8Google Scholar
Banerjee, P. and de Weck, O.L. (2004), “Flexibility strategy-valuing flexible product options”, ICSE Conference on Synergy Between Systems Engineering and Project Management. Las Vegas, NV, INCOSE.Google Scholar
Brahma, A. and Wynn, D.C. (2020a), “Margin value method for engineering design improvement”, Research in Engineering Design, Springer, Vol. 31 No. 3, pp.353–381. 10.1007/s00163-020-00335-8CrossRefGoogle Scholar
Brahma, A. and Wynn, D.C. (2020b), “Calculating target thresholds for the margin value method using computational tools”, Proceedings of the Design Society: DESIGN Conference, Dubrovnik, Croatia Cambridge University Press, Vol. 1, pp. 111–120. 10.1017/dsd.2020.66Google Scholar
Cansler, E. Z., White, S. B., Ferguson, S. M., and Mattson, C. A. (2016). “Excess Identification and Mapping in Engineered Systems. Journal of Mechanical Design, ASME, Vol. 138 No. 8 pp. 081103. 10.1115/1.4033884Google Scholar
Chang, T.-S., Ward, A.C., Lee, J. and Jacox, E.H. (1994), “Conceptual robustness in simultaneous engineering: an extension of Taguchi's parameter design”, Research in Engineering Design, Springer, Vol. 6 No. 4, pp. 211–222. 10.1007/bf01608400Google Scholar
Chen, W., Allen, J.K., Tsui, K.-L. and Mistree, F. (1996), “A Procedure for Robust Design: Minimizing Variations Caused by Noise Factors and Control Factors”, Journal of Mechanical Design, Vol. 118 No. 4, pp. 478–485. 10.1115/1.2826915Google Scholar
Chen, W., Jin, R. and Sudjianto, A. (2006), “Analytical global sensitivity analysis and uncertainty propagation for robust design”, Journal of Quality Technology, Taylor & Francis, Vol. 38 No. 4, pp. 333–348. 10.1080/00224065.2006.11918622CrossRefGoogle Scholar
Chua, D.K.H. and Hossain, M.A. (2012), “Predicting Change Propagation and Impact on Design Schedule Due to External Changes”, IEEE Transactions on Engineering Management, Vol. 59 No. 3, pp. 483–493. 10.1109/tem.2011.2164082Google Scholar
Clarkson, P.J., Simons, C. and Eckert, C. (2004), “Predicting Change Propagation in Complex Design”, Journal of Mechanical Design, ASME, Vol. 126 No. 5, pp. 788–797. 10.1115/1.1765117CrossRefGoogle Scholar
DeVuyst, E.A. and Preckel, P. v. (1997), “Sensitivity analysis revisited: A quadrature-based approach”, Journal of Policy Modeling, Elsevier, Vol. 19 No. 2, pp. 175–185. 10.1016/0161-8938(95)00145-xCrossRefGoogle Scholar
Eckert, C., Clarkson, P.J. and Zanker, W. (2004), “Change and customisation in complex engineering domains”, Research in Engineering Design, Vol. 15 No. 1, pp. 1–21. 10.1007/s00163-003-0031-7Google Scholar
Eckert, C., Isaksson, O. and Earl, C. (2019), “Design margins: a hidden issue in industry”, Design Science, Cambridge University Press, Vol. 5, p. e9. 10.1017/dsj.2019.7Google Scholar
Floricel, S. and Miller, R. (2001), “Strategizing for anticipated risks and turbulence in large-scale engineering projects”, International Journal of Project Management, Elsevier, Vol. 19 No. 8, pp. 445–455. 10.1016/s0263-7863(01)00047-3Google Scholar
Fricke, E., Gebhard, B., Negele, H. and Igenbergs, E. (2000), “Coping with changes: Causes, findings, and strategies”, Systems Engineering, John Wiley & Sons, Inc., Vol. 3 No. 4, pp. 169–179. 10.1002/1520-6858(2000)3:4%3C169::AID-SYS1%3E3.0.CO;2-WGoogle Scholar
Hamraz, B., Hisarciklilar, O., Rahmani, K., Wynn, D.C., Thomson, V. and Clarkson, P.J. (2013), “Change prediction using interface data”, Concurrent Engineering, Vol. 21 No. 2, pp. 141–154. 10.1177/1063293x13482473Google Scholar
Kleizen, H.H. and van Brakel, J. (1984), “On-line measurement techniques in coal-handling systems”, Powder Technology, Vol. 40 No. 1, pp. 113–128. 10.1016/0032-5910(84)85058-5Google Scholar
Lebjioui, S. (2018), Investigating and Managing Design Margins throughout the Product Development Process. [PhD Thesis], Open University, United Kingdom. 10.21954/ou.ro.0000dd57Google Scholar
Lee, S.H. and Chen, W. (2009), “A comparative study of uncertainty propagation methods for black-box-type problems”, Structural and Multidisciplinary Optimization, Springer, Vol. 37 No. 3, p. 239. 10.1007/s00158-008-0234-7Google Scholar
Maier, A. and Langer, S. (2011), Engineering Change Management Report 2011: Survey Results on Causes and Effects, Current Practice, Problems, and Strategies in Denmark. DTU, Copenhagen, Denmark.Google Scholar
McManus, H.L., Hastings, D.E. and Warmkessel, J.M. (2004), “New methods for rapid architecture selection and conceptual design”, Journal of Spacecraft and Rockets, Vol. 41 No. 1, pp. 10–19. 10.2514/1.9203CrossRefGoogle Scholar
Park, G.-J., Lee, T.-H., Lee, K.H. and Hwang, K.-H. (2006), “Robust design: an overview”, AIAA Journal, Vol. 44 No. 1, pp. 181–191. 10.2514/1.13639Google Scholar
Phadke, M.S. (1989), Quality Engineering Using Robust Design, 1st ed., Prentice Hall PTR, USA.Google Scholar
Saleh, J.H., Mark, G. and Jordan, N.C. (2009), “Flexibility: a multi-disciplinary literature review and a research agenda for designing flexible engineering systems”, Journal of Engineering Design, Taylor & Francis, Vol. 20 No. 3, pp. 307–323. 10.1080/09544820701870813CrossRefGoogle Scholar
Sobol, I.M. (2001), “Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates”, Mathematics and Computers in Simulation, Elsevier, Vol. 55 No. 1–3, pp. 271–280. 10.1016/s0378-4754(00)00270-6Google Scholar
Suh, N.P. (2001), Axiomatic Design: Advances and Applications, Oxford University Press, UK.Google Scholar
Taguchi, G. and Clausing, D. (1990), “Robust Quality.”, Harvard Business Review, Vol. 68 No. 1, pp. 65–75. Available at: https://hbr.org/1990/01/robust-qualityGoogle Scholar
Terwiesch, C. and Loch, C.H. (1999), “Managing the Process of Engineering Change Orders: The Case of the Climate Control System in Automobile Development”, Journal of Product Innovation Management, Blackwell Publishing, Vol. 16 No. 2, pp. 160–172. 10.1016/S0737-6782(98)00041-1Google Scholar