Skip to main content
SpringerLink
Log in

A Fuzzy Multiphase and Multicriteria Decision-Making Method for Cutting Technologies Used in Shipyards

  • Published:
International Journal of Fuzzy Systems Aims and scope Submit manuscript

Abstract

Cutting operation is one of the most significant processes in shipbuilding. In the shipyard industry, there are various cutting technologies and the selection of the appropriate cutting technology for the production process is a serious engineering problem. The main aim of this study is to find out the most appropriate cutting technique for shipyard industry by considering conflicting factors such as cost, risk, and performance. An integrated method including fuzzy, analytic hierarchy process, information axiom, and technique for order performance by similarity to ideal solution has been utilized for the evaluation procedure. Oxy-fuel technology is determined as the most appropriate cutting technology for shipyard industry.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

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

Similar content being viewed by others

References

  1. Celik, M., Cebi, S., Kahraman, C., Er, I.D.: Application of axiomatic design and TOPSIS methodologies under fuzzy environment for proposing competitive strategies on Turkish container ports in maritime transportation network. Expert Syst. Appl. 36(3), 4541–4557 (2009)

    Article  Google Scholar 

  2. Ozkok, M., Cebi, S.: A fuzzy based assessment method for comparison of ship launching method. J. Intell. Fuzzy Syst. 26, 781–791 (2014)

    Google Scholar 

  3. Zadeh, L.A.: Fuzzy sets. Inf. Control 8, 338–353 (1965)

    Article  MathSciNet  MATH  Google Scholar 

  4. Lu, J., Zhang, G., Ruan, D., Wu, F.: Multi-Objective Group Decision Making, Methods, Software and Applications with Fuzzy Set Techniques. Imperial College Press, London (2007)

    Book  MATH  Google Scholar 

  5. Yen, J., Langari, R.: Fuzzy Logic; Intelligence, Control and Information. Prentice Hall, Upper Saddle River (1998)

    Google Scholar 

  6. Zheng, H.Y., Han, Z.Z., Chen, Z.D., Chena, W.L., Yeo, S.: Quality and cost comparisons between laser and waterjet cutting. J. Mater. Process. Technol. 62, 294–298 (1996)

    Article  Google Scholar 

  7. Syn, C.Z., Mokhtar, M., Feng, C.J., Manurung, Y.H.P.: Approach to prediction of laser cutting quality by employing fuzzy expert system. Expert Syst. Appl. 38, 7558–7568 (2011)

    Article  Google Scholar 

  8. Stournaras, A., Stavropoulos, P., Salonitis, K., Chryssolouris, G.: An investigation of quality in CO2 laser cutting of aluminum. CIRP J. Manuf. Sci. Technol. 2, 61–69 (2009)

    Article  Google Scholar 

  9. Dubey, A.K., Yadava, V.: Laser beam machining—a review. Int. J. Mach. Tools Manuf. 48, 609–628 (2007)

    Article  Google Scholar 

  10. Thomas, D.J.: The influence of the laser and plasma traverse cutting speed process parameter on the cut-edge characteristics and durability of Yellow Goods vehicle applications. J. Manuf. Process 13, 120–132 (2011)

    Article  Google Scholar 

  11. Ebadian, M.A., Dua, S.K., Guha, H.: Size distribution and rate of production of airborne particulate matter generated during metal cutting. Hemispheric Center For Environmental Technology (HCET), Report, Miami (2001)

  12. Kafali, M., Ozkok, M., Cebi, S.: Evaluation of pipe cutting technologies in shipbuilding. Brodogr. Shipbuild. 65(2), 33–48 (2014)

    Google Scholar 

  13. Porter, J.A., Louhisalmi, Y.A., Karjalainen, J.A., Füger, S.: Cutting thin sheet metal with a water jet guided laser using various cutting distances, feed speeds and angles of incidence. Int. J. Adv. Manuf. Technol. 33, 961–967 (2007)

    Article  Google Scholar 

  14. Olsen, F.O.: Laser metal cutting with tailored beam patterns. Technology Report, Industrial Laser Solutions, pp. 17–19 (2011)

  15. Ozek, C., Caydas, U., Unal, E.: A fuzzy model for predicting surface roughness in plasma arc cutting of AISI 4140 steel. Mater. Manuf. Process 27(1), 95–102 (2011)

    Article  Google Scholar 

  16. McCormick, G.: Comparing abrasive waterjet cutting technology to other methods, DEMM: Eng. Manuf. 12–13 (2009)

  17. Akkurt, A.: Comparison of cut surface properties obtained from AISI 1030 steel by abrasive water jet and by other methodologies. Pamukkale Univ. Eng. Sci. Mag. 15(2), 142–152 (2009)

    Google Scholar 

  18. Mäntyjärvi, K., Väisänen, A., Karjalainen, J.A.: Cutting method influence on the fatigue resistance of ultra-high-strength steel. Int. J. Mater. Form. 2(1), 547–550 (2009)

    Article  Google Scholar 

  19. Meurling, F., Melander, A., Linder, J., Larsson, M.: The influence of mechanical and laser cutting on the fatigue strengths of carbon and stainless sheet steels. Scand. J. Metall. 30(5), 309–319 (2001)

    Article  Google Scholar 

  20. Betts, B.: The kindest cut [laser and water cutting]. Eng. Technol. 5, 57–59 (2010)

    Google Scholar 

  21. Metal Center News: Thermal and waterjet cutting. The Cutting Edge, vol. 44, pp. 8–9. http://connection.ebscohost.com/c/articles/14701581/thermal-waterjet-cutting (2004)

  22. Harničárová, M., Zajac, J., Stoić, A.: Comparison of different material cutting technologies in terms of their impact on the cutting quality of structural steel. Tech. Gaz. 17(3), 371–376 (2010)

    Google Scholar 

  23. Arasaratnam, P., Sivakumaran, K.S., Rasmussen, K.J.R.: Measurement and assessment of imperfections in plasma cut-welded H-shaped steel columns. Steel Compos. Struct. 6(6), 531–555 (2006)

    Article  Google Scholar 

  24. Atici, U., Gullu, A.: A comparison of the effects of plasma and underwater plasma arc methods on surface roughness and hardness variations of AISI 304 and AISI 1050 steels. G.U. J. Sci. 18(4), 647–655 (2005)

    Google Scholar 

  25. Hypertherm Inc. Plasma, oxyfuel, laser: which fits you best? The Cutting Edge. pp. 2–4 (2009)

  26. Yazicioglu, O., Yalcinkaya, S.: Designs of abrasive water jet in industry. Eng. Mach. 522, 44–48 (2003)

  27. Koike, H.: Laser bevel cutting in Japan’s shipyards. Application Report, Industrial Laser Solutions, pp. 4–8 (2009)

  28. Geiger, M., Kach, A., Hohenstein, R., Maros, Z.: Fuzzy-logic based knowledge representation for water jet cutting of light-weight composites. Mach. Sci. Technol. 7(3), 349–360 (2003)

    Article  Google Scholar 

  29. Taniki, D., Mani, M., Devedži, G., Stevi, Z.: Modelling metal cutting parameters using intelligent techniques. Stroj. Vestnik J. Mech. Eng. 56(1), 52–62 (2010)

    Google Scholar 

  30. Yilbas, B.S.: The analysis of CO2 laser cutting. Proc. Inst. Mech. Eng. 211(Part B), 223–232 (1997)

    Article  Google Scholar 

  31. Kutlu, A.E., Monno, M., Bini, R.: General view to cutting method with plasma. Eng. Mach. 46(541), 21–29 (2005)

    Google Scholar 

  32. Geren, N., Tunc, T.: Determination of the most appropriate one between waterjet cutting systems which are structural different. Eng. Mach. 42(500), 42–49 (2001)

    Google Scholar 

  33. Chen, S.M.: Aggregating fuzzy opinions in the decision-making environment. Cybern. Syst. Int. J. 29, 363–376 (1998)

    Article  MATH  Google Scholar 

  34. Li, Y., Liu, X.D., Chen, Y.: Supplier evaluation and selection using axiomatic fuzzy set and DEA methodology in supply chain management. Int. J. Fuzzy Syst. 14(2), 215–225 (2012)

    Google Scholar 

  35. Chen, S.J., Hwang, C.L.: Fuzzy Multi Attribute Decision Making: Methods and Applications. Springer, New York (1992)

    Book  Google Scholar 

  36. Opricovic, S., Tzeng, G.H.: Compromise solution by MCDM methods: a comparative analysis of VIKOR and TOPSIS. Eur. J. Oper. Res. 156(2), 445–455 (2004)

    Article  MATH  Google Scholar 

  37. Kahraman, C., Cebi, S.: A new multi-attribute decision making method: hierarchical fuzzy axiomatic design. Expert Syst. Appl. 34, 1603–1616 (2009)

    Google Scholar 

  38. Kulak, O., Kahraman, C.: Fuzzy multi-attribute selection among transportation companies using axiomatic design and analytic hierarchy process. Inf. Sci. 170, 191–210 (2005)

    Article  MATH  Google Scholar 

  39. Kulak, O., Kahraman, C.: Multi-attribute comparison of advanced manufacturing systems using fuzzy vs. crisp axiomatic design approach. Int. J. Prod. Econ. 95, 415–424 (2005)

    Article  Google Scholar 

  40. Suh, N.P.: The Principles Of Design. Oxford University Press, New York (1990)

    Google Scholar 

  41. Suh, N.P.: Axiomatic Design, Advanced Applications. Oxford University Press, New York (2001)

    Google Scholar 

  42. Suh, N.P.: Complexity Theory and Applications. Oxford University Press, New York (2005)

    Google Scholar 

  43. Cebi, S., Kahraman, C.: Developing a group decision support system based on fuzzy information axiom. Knowl. Based Syst. 23(1), 3–16 (2010)

    Article  Google Scholar 

  44. Chen, T.-C.: Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets Syst. 114, 1–9 (2000)

    Article  MATH  Google Scholar 

  45. Hsieh, T.Y., Lu, S.T., Tzeng, G.T.: Fuzzy MCDM approach for planning and design tenders selection in public office buildings. Int. J. Proj. Manag. 22, 573–584 (2004)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Industrial Engineering, Yildiz Technical University, Istanbul, Turkey

    Selcuk Cebi

  2. Department of Naval Architecture and Marine Engineering, Karadeniz Technical University, Trabzon, Turkey

    Murat Ozkok

  3. Department of Naval Architecture and Marine Engineering, Istanbul Technical University, Istanbul, Turkey

    Mustafa Kafali

  4. Department of Industrial Engineering, Istanbul Technical University, Istanbul, Turkey

    Cengiz Kahraman

Authors
  1. Selcuk Cebi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Murat Ozkok
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mustafa Kafali
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Cengiz Kahraman
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Selcuk Cebi.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cebi, S., Ozkok, M., Kafali, M. et al. A Fuzzy Multiphase and Multicriteria Decision-Making Method for Cutting Technologies Used in Shipyards. Int. J. Fuzzy Syst. 18, 198–211 (2016). https://doi.org/10.1007/s40815-015-0085-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40815-015-0085-5

Keywords

Search

Navigation