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Applications of the MOORA method for decision making in manufacturing environment

  • Shankar ChakrabortyEmail author
ORIGINAL ARTICLE

Abstract

To meet the challenges of global competitiveness, manufacturing organizations are now facing the problems of selecting appropriate manufacturing strategies, product and process designs, manufacturing processes and technologies, and machinery and equipment. The selection decisions become more complex as the decision makers in the manufacturing environment have to assess a wide range of alternatives based on a set of conflicting criteria. To aid these selection processes, various multi-objective decision-making (MODM) methods are now available. This paper explores the application of an almost new MODM method, i.e., the multi-objective optimization on the basis of ratio analysis (MOORA) method to solve different decision-making problems as frequently encountered in the real-time manufacturing environment. Six decision-making problems which include selection of (a) an industrial robot, (b) a flexible manufacturing system, (c) a computerized numerical control machine, (d) the most suitable non-traditional machining process for a given work material and shape feature combination, (e) a rapid prototyping process, and (f) an automated inspection system are considered in this paper. In all these cases, the results obtained using the MOORA method almost corroborate with those derived by the past researchers which prove the applicability, potentiality, and flexibility of this method while solving various complex decision-making problems in present day manufacturing environment.

Keywords

Decision making MOORA method Industrial robot Flexible manufacturing system Machine tool Non-traditional machining process Rapid prototyping Automated inspection system 

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References

  1. 1.
    Brauers WKM (2004) Optimization methods for a stakeholder society. A revolution in economic thinking by multiobjective optimization. Kluwer Academic Publishers, BostonGoogle Scholar
  2. 2.
    Brauers WKM, Zavadskas EK, Peldschus F, Turskis Z (2008) Multi-objective decision-making for road design. Transport 23:183–193CrossRefGoogle Scholar
  3. 3.
    Brauers WKM, Zavadskas EK (2009) Robustness of the multi-objective MOORA method with a test for the facilities sector. Technological and Economic Development of Economy: Baltic J on Sustainability 15:352–375CrossRefGoogle Scholar
  4. 4.
    Brauers WKM, Zavadskas EK (2006) The MOORA method and its application to privatization in a transition economy. Control Cybern 35:445–469MathSciNetzbMATHGoogle Scholar
  5. 5.
    Brauers WKM (2008) Multi-objective contractor’s ranking by applying the MOORA method. J of Business Economics and Management 4:245–255CrossRefGoogle Scholar
  6. 6.
    Brauers WKM, Zavadskas EK, Peldschus F, Turskis Z (2008) Multi-objective optimization of road design alternatives with an application of the MOORA method, Proc of the 25th Int Sym on Automation and Robotics in Construction, Lithuania, 541–548Google Scholar
  7. 7.
    Kalibatas D, Turskis Z (2008) Multicriteria evaluation of inner climate by using MOORA method. Inf Tech and Con 37:79–83Google Scholar
  8. 8.
    Lootsma FA (1999) Multi-criteria decision analysis via ratio and difference judgement. Springer, LondonzbMATHCrossRefGoogle Scholar
  9. 9.
    Bhangale PP, Agrawal VP, Saha SK (2004) Attribute based specification, comparison and selection of a robot. Mech Mach Theory 39:1345–1366zbMATHCrossRefGoogle Scholar
  10. 10.
    Rao RV (2007) Decision making in the manufacturing environment using graph theory and fuzzy multiple attribute decision making methods. Springer, LondonGoogle Scholar
  11. 11.
    Karsak EE, Kuzgunkaya O (2002) A fuzzy multiple objective programming approach for the selection of a flexible manufacturing system. Int J Prod Eco 79:101–111CrossRefGoogle Scholar
  12. 12.
    Rao RV, Parnichkun M (2008) Flexible manufacturing system selection using a combinatorial mathematics-based decision-making method. Int J Prod Res 47:6981–6998CrossRefGoogle Scholar
  13. 13.
    Sun S (2002) Assessing computer numerical control machines using data envelopment analysis. Int J Prod Res 40:2011–2039zbMATHCrossRefGoogle Scholar
  14. 14.
    Yurdakul M, Cogun C (2003) Development of a multi-attribute selection procedure for non-traditional machining processes. Proc IMechE, J of Engg Manuf 217:993–1009CrossRefGoogle Scholar
  15. 15.
    Das Chakladar N, Chakraborty S (2008) A combined TOPSIS-AHP method based approach for non-traditional machining processes selection. Proc IMechE, J of Engg Manuf 222:1613–1623CrossRefGoogle Scholar
  16. 16.
    Daschakladar N, Das R, Chakraborty S (2009) A digraph-based expert system for non-traditional machining processes selection. Int J Adv Manuf Tech 43:226–237CrossRefGoogle Scholar
  17. 17.
    Byun HS, Lee KS (2004) A decision support system for the selection of a rapid prototyping process using the modified TOPSIS method. Int J Adv Manuf Tech 26:1338–1347CrossRefGoogle Scholar
  18. 18.
    Rao RV, Patel BK (2009) Decision making in the manufacturing environment using an improved PROMETHEE method. Int J Prod Res 48:4665–4682Google Scholar
  19. 19.
    Pandey PC, Kengpol A (1995) Selection of an automated inspection system using multiattribute decision analysis. Int J Prod Econ 39:289–298CrossRefGoogle Scholar
  20. 20.
    Ginevičius R, Podvezko V (2008) Multi-criteria graphical-analytical evaluation of the financial state of construction enterprises. Baltic J on Sustainability 14:452–461CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Limited 2010

Authors and Affiliations

  1. 1.Department of Production EngineeringJadavpur UniversityKolkataIndia

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