Hostname: page-component-78c5997874-t5tsf Total loading time: 0 Render date: 2024-11-11T05:34:45.120Z Has data issue: false hasContentIssue false

CALCULATING TARGET THRESHOLDS FOR THE MARGIN VALUE METHOD USING COMPUTATIONAL TOOLS

Published online by Cambridge University Press:  11 June 2020

A. Brahma*
Affiliation:
The University of Auckland, New Zealand
D. C. Wynn
Affiliation:
The University of Auckland, New Zealand

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.

Overspecification or excess margin in a design can enhance its ability to absorb changes and uncertainty, but also deteriorates performance criteria such as weight and cost. This paper shows how the Margin Value Method (article in review) can be applied in conjunction with CAE tools such as FEA to quantify excess margin where a design is too complex for algebraic analysis. This new application context for the MVM is illustrated using a case study of a flange coupling design, in which topology optimisation is used within the MVM to identify opportunities for design improvement.

Type
Article
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), 2020. Published by Cambridge University Press

References

Bhandari, V.B. (2010), Design of Machine Elements, 3rd ed., Tata McGraw-Hill, India.Google Scholar
Brahma, A. and Wynn, D.C. (2019), Margin value method for engineering design improvement.CrossRefGoogle Scholar
Budynas, R.G. and Nisbett, J.K. (2014), Shigley's Mechanical Engineering Design, McGraw-Hill Higher Education, NY.Google Scholar
Cansler, E.Z. et al. (2016), “Excess Identification and Mapping in Engineered Systems”, Journal of Mechanical Design, Vol. 138 No. 8, p. 081103. https://doi.org/10.1115/1.4033884CrossRefGoogle Scholar
Clarkson, P.J., Simons, C. and Eckert, C. (2004), “Predicting Change Propagation in Complex Design”, Journal of Mechanical Design, Vol. 126 No. 5, pp. 788797.CrossRefGoogle Scholar
Collins, J.A. (2010), Mechanical design of machine elements and machines: a failure prevention perspective, 2nd ed., Wiley, Hoboken, NJ. https://doi.org/10.1115/1.1635406Google 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. 121. https://doi.org/10.1007/s00163-003-0031-7CrossRefGoogle Scholar
Eckert, C. and Isaksson, O. (2017), “Safety Margins and Design Margins: A Differentiation between Interconnected Concepts”, Procedia CIRP, Vol. 60, pp. 267272. https://doi.org/10.1016/j.procir.2017.03.140CrossRefGoogle Scholar
Fenton, G.A. et al. (2015), “Reliability-based geotechnical design in 2014 Canadian highway bridge design code”, Canadian Geotechnical Journal, Vol. 53 No. 2, pp. 236251. https://doi.org/10.1139/cgj-2015-0158CrossRefGoogle Scholar
Ghosn, M. and Moses, F. (1986), “Reliability calibration of bridge design code”, Journal of Structural Engineering, Vol. 112, No. 4, pp. 745763. https://doi.org/10.1061/(asce)0733-9445(1986)112:4(745)CrossRefGoogle Scholar
Guenov, M.D. et al. (2018), “Margin Allocation and Tradeoff in Complex Systems Design and Optimization”, AIAA Journal, Vol. 56 No. 7, pp. 28872902. https://doi.org/10.2514/1.j056357CrossRefGoogle Scholar
Iorga, C., Desrochers, A. and Smeesters, C. (2012), “Engineering design from a safety perspective”, Proceedings of the Canadian Engineering Education Association Conference. University of Manitoba. June 17-20, 2012. https://doi.org/10.24908/pceea.v0i0.4654CrossRefGoogle Scholar
Lebjioui, S. (2018), Investigating and Managing Design Margins throughout the Product Development Process, The Open University.Google Scholar
Mohammed, E.A. et al. (2016), “Design safety margin of a 10,000 TEU container ship through ultimate hull girder load combination analysis”, Marine Structures, Vol. 46, pp. 78101. https://doi.org/10.1016/j.marstruc.2015.12.003CrossRefGoogle Scholar
Morse, E. et al. (2018), “Tolerancing: Managing uncertainty from conceptual design to final product”, CIRP Annals - Manufacturing Technology, Vol. 67 No. 2, pp. 695717. https://doi.org/10.1016/j.cirp.2018.05.009CrossRefGoogle Scholar
Tackett, M.W.P., Mattson, C.A. and Ferguson, S.M. (2014), “A Model for Quantifying System Evolvability Based on Excess and Capacity”, Journal of Mechanical Design, Vol. 136, pp. 5. https://doi.org/10.1115/1.4026648CrossRefGoogle Scholar
Tan, J., Otto, K. and Wood, K. (2016), “Concept Design Trade-Offs Considering Performance Margins”, in Boks, C., Sigurjonsson, J., Steinert, M., Vis, C. and Wulvik, A. (Eds) DS 85-1: Proceedings of NordDesign 2016, Volume 1, Trondheim, Norway, 10th-12th August 2016, p. 421.Google Scholar
Tilstra, A.H. et al. (2015), “Principles for designing products with flexibility for future evolution”, International Journal of Mass Customisation, Vol. 5 No. 1, pp. 2254. https://doi.org/10.1504/ijmassc.2015.069597CrossRefGoogle Scholar
Watson, J.D. et al. (2016), “Optimization of excess system capability for increased evolvability”, Structural and Multidisciplinary Optimization, Vol. 53 No. 6, pp. 12771294. https://doi.org/10.1007/s00158-015-1378-xCrossRefGoogle Scholar
Zhu, J. and Ting, K. (2000), “Performance Distribution Analysis and Robust Design”, Journal of Mechanical Design, Vol. 123 No. 1, pp. 1117. https://doi.org/10.1115/1.1333095CrossRefGoogle Scholar