Journal of Marine Science and Technology

, Volume 16, Issue 1, pp 68–75 | Cite as

Ship complexity assessment at the concept design stage

Original Article

Abstract

An innovative complexity metric is introduced that provides a way to compare similar or different ship types and sizes at the contract design stage. The goal is to provide the designer with this information throughout the design process so that an efficient design is obtained during the first design run. Application to and validation on real passenger ships indicate that there is a significant correlation between the error in an engineer’s judgement of complexity and the cost assessment error. It follows that this tool could be used to improve knowledge of the ship’s complexity at the contract design stage, and even to try to optimise the design if the complexity criteria are not fixed by the shipowners.

Keywords

Design complexity Shipbuilding Cost assessment Optimisation 

Notes

Acknowledgments

The authors thank the University of Liege and experts at some European shipyards for their collaboration with this project, as well as the Belgian National Funds of Scientific Research (NFSR) for their financial support.

References

  1. 1.
    Simon HA (1962) The architecture of complexity. Proc Am Philos Soc 106:467–482Google Scholar
  2. 2.
    Simon H (1996) The sciences of the artificial. MIT Press, CambridgeGoogle Scholar
  3. 3.
    Rodriguez-Toro C, Tate S, Jared G, Swift K (2003) Complexity metrics for design. Proc Inst Mech Eng B 217:721–725Google Scholar
  4. 4.
    Chryssolouris G (1994) Measuring complexity in manufacturing systems (technical report). University of Patras, PatrasGoogle Scholar
  5. 5.
    Little G, Tuttle D, Clark DER, Corney J (1997) A feature complexity index. Proc Inst Mech Eng C 212:405–412Google Scholar
  6. 6.
    Calinescu A, Efstathiou J, Sivadasan S, Schirn J, Huaccho HL (2000) Complexity in manufacturing: an information theoretic approach. In: Conference on complexity and complex systems in industry. University of Warwick, Warwick, 19–20 Sept 2000, pp 19–20Google Scholar
  7. 7.
    Tang V, Salminen V (2001) Towards a theory of complicatedness: framework for complex systems analysis and design. In: 13th International conference on engineering design, Glasgow, UK, 21–23 August 2001, p 8Google Scholar
  8. 8.
    Community of European Shipyards Associations (CESA), the Shipbuilders’ Association of Japan (SAJ) and the Korean Shipbuilders Association (KSA) (2007) Compensated gross ton (CGT) system (technical report). Organisation for Economic Co-Operation and Development (OECD), Paris. http://www.oecd.org/dataoecd/59/49/37655301.pdf
  9. 9.
    Bertram V (2003) Strategic control of productivity and other competitiveness parameters. Proc Inst Mech Eng M 217:61–70Google Scholar
  10. 10.
    Bruce GJA (2006) A review of the use of compensated gross tonnage for shipbuilding performance measurement. J Ship Product 22:99–104Google Scholar
  11. 11.
    Lamb T (2003) Methodology used to calculate naval compensated gross tonnage factors. J Ship Product 19:29–30Google Scholar
  12. 12.
    Brans J, Mareschal B (1992) PROMETHEE V: MCDM problems with segmentation constraints. INFOR 30:85–96Google Scholar
  13. 13.
    Brans J, Mareschal B (1994) How to decide with PROMETHEE. http://www.visualdecision.com/Pdf/How%20to%20use%20PROMETHEE.pdf
  14. 14.
    Brans J-P, Mareschal B (2005) PROMOTHEE methods. In: Figueira J, Greco S, Ehrgott M (eds) Multiple criteria decision analysis: state of the art surveys. Springer, New York, 78:163–186Google Scholar

Copyright information

© JASNAOE 2010

Authors and Affiliations

  1. 1.ANASTUniversity of LiègeLiègeBelgium

Personalised recommendations