Skip to main content
Log in

Margin value method for engineering design improvement

  • Original Paper
  • Published:
Research in Engineering Design Aims and scope Submit manuscript

Abstract

Margin occurs where a design is overspecified with respect to the minimum required. Margin may be desirable to mitigate risk and absorb future changes, but at the same time, may be undesirable if the overspecification deteriorates the design’s performance. In this article, the margin value method (MVM) is introduced to analyse an engineering design, localise the excess margin, and quantify it considering change absorption potential in relation to design performance deterioration. The method provides guidance for improving a design by prioritising excess margin that provides relatively little advantage at high cost, and that could, therefore, be eliminated to improve design performance. It shows how the value of excess margin depends on its localisation in the design parameter network, the importance of design performance parameters, and the importance of absorbing potential future changes. The method is applied to a belt conveyor design. This case indicates that the method is practicable, reveals implications, and suggests opportunities for further work.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  • Ahmad N, Wynn DC, Clarkson PJ (2013) Change impact on a product and its redesign process: a tool for knowledge capture and reuse. Res Eng Des 24(3):219–244

    Article  Google Scholar 

  • Albers A, Braun A, Sadowski E, Wynn DC, Wyatt DF, Clarkson PJ (2011) System architecture modeling in a software tool based on the contact and channel approach (C&C-A). J Mech Des 133(10):101–006

    Article  Google Scholar 

  • Allen JD, Stevenson PD, Mattson CA, Hatch NW (2019) Over-design versus redesign as a response to future requirements. J Mech Des 141(3):031,101–031,101–13

    Article  Google Scholar 

  • API (1991) Recommended practice for design and installation of offshore production platform piping systems (RP14E)

  • B313 A (2002) Process piping

  • Baldwin CY, Clark KB (2000) Design rules: the power of modularity. MIT, Cambridge

    Book  Google Scholar 

  • Becht C IV (2009) Pressure testing. ASME, New York

    Book  Google Scholar 

  • Cansler EZ, White SB, Ferguson SM, Mattson CA (2016) Excess identification and mapping in engineered systems. J Mech Des 138(8):081–103

    Article  Google Scholar 

  • Chua DKH, Hossain MA (2012) Predicting change propagation and impact on design schedule due to external changes. IEEE Trans Eng Manage 59(3):483–493

    Article  Google Scholar 

  • Clarkson PJ, Simons C, Eckert C (2004) Predicting change propagation in complex design. J Mech Des 126(5):788–797

    Article  Google Scholar 

  • Collins JAJA (2010) Mechanical design of machine elements and machines: a failure prevention perspective, 2nd edn. Wiley, Hoboken

    Google Scholar 

  • Dittmar R, Hartmann K (1976) Calculation of optimal design margins for compensation of parameter uncertainty. Chem Eng Sci 31(7):563–568

    Article  Google Scholar 

  • Eckert C, Isaksson O (2017) Safety margins and design margins: a differentiation between interconnected concepts. Procedia CIRP 60:267–272

    Article  Google Scholar 

  • Eckert C, Clarkson PJ, Zanker W (2004) Change and customisation in complex engineering domains. Res Eng Des 15(1):1–21

    Article  Google Scholar 

  • Eckert C, Isaksson O, Earl C (2012) Product property margins: an underlying critical problem of engineering design. Proc TMCE 2012:1027–1040

    Google Scholar 

  • Eckert C, Earl C, Lebjioui S, Isaksson O (2013) Components margins through the product lifecycle. In: Bernard A, Rivest L, Dutta D (eds) Product lifecycle management for society. Springer, Berlin, pp 39–47

    Chapter  Google Scholar 

  • Eckert C, Isaksson O, Earl C (2019) Design margins: a hidden issue in industry. Des Sci 5:e9. https://doi.org/10.1017/dsj.2019.7

    Article  Google Scholar 

  • Fenton GA, Naghibi F, Dundas D, Bathurst RJ, Griffiths DV (2015) Reliability-based geotechnical design in 2014 canadian highway bridge design code. Can Geotech J 53(2):236–251

    Article  Google Scholar 

  • Gale PA (1975) Margins in naval surface ship design. Naval Eng J 87(2):174–188

    Article  Google Scholar 

  • Ghosn M, Moses F (1986) Reliability calibration of bridge design code. J Struct Eng 112(4):745–763

    Article  Google Scholar 

  • Gimenez M, Schlamp M, Vertullo A (2002) Uncertainties assessment for safety margins evaluation in mtr reactors core thermal-hydraulic design. Tech. Rep. INIS-XA-C–001, International Atomic Energy Agency (IAEA)

  • Guenov MD, Chen X, Molina-Cristobal A, Riaz A, van Heerden ASJ, Padulo M (2018) Margin allocation and tradeoff in complex systems design and optimization. AIAA J 56(7):2887–2902

    Article  Google Scholar 

  • Hammer W (1980) Product safety management and engineering. Prentice-Hall international series in industrial and systems engineering. Prentice-Hall, Englewood Cliffs

    Google Scholar 

  • Hamraz B, Caldwell NHM, Clarkson PJ (2013a) A holistic categorization framework for literature on engineering change management. Syst Eng 16(4):473–505

    Article  Google Scholar 

  • Hamraz B, Hisarciklilar O, Rahmani K, Wynn DC, Thomson V, Clarkson PJ (2013b) Change prediction using interface data. Concurr Eng 21(2):141–154

    Article  Google Scholar 

  • Hockberger WA (1976) Ship design margins–issues and impacts. Naval Eng J 88(2):157–170

    Article  Google Scholar 

  • Iorga C, Desrochers A, Smeesters C (2012) Engineering design from a safety perspective. In: 2012: Proceedings of the Canadian engineering education association conference. University of Manitoba June 17–20, 2012

  • Jones DA, Eckert CM, Gericke K (2018) Margins leading to over-capacity. In: Marjanović D, Štorga M, Škec S, Bojčetić N, Pavković N (eds) DS 92: Proceedings of the DESIGN 2018 15th international design conference, the design society, pp 781–792

  • Juvinall RC, Marshek KM (1991) Fundamentals of machine component design, 2nd edn. Wiley, New York

    Google Scholar 

  • Lebjioui S (2018) Investigating and managing design margins throughout the product development process. PhD thesis, The Open University

  • Levine G, Hawkins S (1970) Comments on service margins for ships. Naval Eng J 82(5):75–86

    Article  Google Scholar 

  • Lusser R (1958) Reliability through safety margins. Tech. rep., Research and Development Division, Army Rocket and Guided Missile Agency, Redstone Arsenal, Alabama

  • Ma S, Jiang Z, Liu W (2017) A design change analysis model as a change impact analysis basis for semantic design change management. Proc Inst Mech Eng Part C J Mech Eng Sci 231(13):2384–2397

    Article  Google Scholar 

  • Martin MV, Ishii K (2002) Design for variety: developing standardized and modularized product platform architectures. Res Eng Des 13(4):213–235

    Article  Google Scholar 

  • Mohammed EA, Benson S, Hirdaris S, Dow R (2016) Design safety margin of a 10,000 TEU container ship through ultimate hull girder load combination analysis. Mar Struct 46:78–101

    Article  Google Scholar 

  • Moller N, Hansson SO (2008) Principles of engineering safety: risk and uncertainty reduction. Reliab Eng Syst Saf 93(6):798–805

    Article  Google Scholar 

  • Morse E, Dantan JY, Anwer N, Söderberg R, Moroni G, Qureshi A, Jiang X, Mathieu L (2018) Tolerancing: managing uncertainty from conceptual design to final product. CIRP Ann 67(2):695–717

    Article  Google Scholar 

  • Oloufa AA, Hosni YA, Fayez M, Axelsson P (2004) Using dsm for modeling information flow in construction design projects. Civ Eng Environ Syst 21(2):105–125

    Article  Google Scholar 

  • Otto KN, Wood K (2003) Product design: techniques in reverse engineering and new product development. Prentice Hall, Upper Saddle River

    Google Scholar 

  • Pilch M, Trucano TG, Helton JC (2011) Ideas underlying the quantification of margins and uncertainties. Reliab Eng Syst Saf 96(9):965–975

    Article  Google Scholar 

  • Saaty TL (1988) What is the analytic hierarchy process? In: Mathematical models for decision support, Springer, pp 109–121

  • Snape S, Whittle S, Sen P, Rajabally E (2005) Margins of performance in engineering: The requirement for a systematic approach. In: Samuel A, Lewis W (eds) DS 35: Proceedings ICED 05, the 15th international conference on engineering design, Melbourne, Australia, 15.-18.08. 2005

  • Stephenson J, Callander RA (1974) Engineering design. Wiley, Sydney

    Google Scholar 

  • Tackett MWP, Mattson CA, Ferguson SM (2014) A model for quantifying system evolvability based on excess and capacity. J Mech Des 136(5):051,002–051,002–11

    Article  Google Scholar 

  • Takamatsu T, Hashimoto I, Shioya S (1974) On design margin for process system with parameter uncertainty. J Chem Eng Jpn 6(5):453–457

    Article  Google Scholar 

  • Tan J, Otto K, Wood K (2016) Concept design trade-offs considering performance margins. In: Boks C, Sigurjonsson J, Steinert M, Vis C, Wulvik A (eds) DS 85-1: Proceedings of NordDesign 2016, Volume 1, Trondheim, Norway, 10th–12th August 2016, pp 421–429

  • Thunnissen DP, Tsuyuki GT (2004) Margin determination in the design and development of a thermal control system. In: International conference on environmental systems, SAE International

  • Thunnissen DP (2004) Method for determining margins in conceptual design. J Spacecr Rock 41(1):85–92

    Article  Google Scholar 

  • Tilstra AH, Backlund PB, Seepersad CC, Wood KL (2015) Principles for designing products with flexibility for future evolution. Int J Mass Custom 5(1):22–54

    Article  Google Scholar 

  • Watson JD, Allen JD, Mattson CA, Ferguson SM (2016) Optimization of excess system capability for increased evolvability. Struct Multidiscip Optim 53(6):1277–1294

    Article  Google Scholar 

  • Zhu J, Ting KL (2000) Performance distribution analysis and robust design. J Mech Des 123(1):11–17

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Arindam Brahma.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendices

Appendix 1: Definitions for the hydraulic circuit

Input parameters

  • h = Maximum height the mass is to be lifted;

  • \(d_{\text {ext}}\) = Maximum external diameter of the cylinder that can be accommodated;

  • m = Mass to be lifted by the hydraulic system;

Performance parameter

  • \(P_{\text {D}}\) = Design/Operating pressure of the system;

Intermediary parameters

  • \(P_{\text {R}}\) = Required pressure to lift mass m (target threshold);

  • \(P_{\text {M}}\) = Maximum pressure the pump can generate (decided value);

  • \(P_{\text {V}}\) = Max pressure the valve can handle (decided value);

  • \(P_{\text {C}}\) = Max pressure the cylinder can handle (decided value);

  • \(C_{\text {M}}\) = Cylinder model number (decided value);

  • \(C_{\text {W}}\) = Mass of the selected cylinder (decided value);

  • \(d_{\text {bore}}\) = Bore diameter of the selected cylinder (decided value);

  • \(M_{\text {M}}\) = Pump model number (decided value);

  • \(M_{\text {GD}}\) =Pump mount dimensions (decided value);

  • \(M_{\text {CP}}\) = Pump electrical power consumption (decided value);

  • \(M_{\text {W}}\) = Pump mass (decided value);

  • \(V_{\text {TS}}\) = Valve thread size (decided value);

  • \(V_{\text {M}}\) = Valve model number (decided value);

  • \(V_{\text {W}}\) = Valve mass (decided value);

Appendix 2: Definitions for the belt conveyor case

See Tables 2, 3, 4, 5, and 6.

Table 2 Definitions of input parameters and their nominal values for the belt conveyor case, organised alphabetically. Input parameters considered in the MVA are indicated in bold
Table 3 Definitions of parameters used in the belt conveyor case, except for input, decision, and performance parameters
Table 4 Definitions of margin nodes, their decided values and target thresholds for the belt conveyor case
Table 5 Definitions of performance parameters and their calculation for the belt conveyor case
Table 6 Definitions of decisions and their output parameters for the belt conveyor case

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Brahma, A., Wynn, D.C. Margin value method for engineering design improvement. Res Eng Design 31, 353–381 (2020). https://doi.org/10.1007/s00163-020-00335-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00163-020-00335-8

Keywords

Navigation