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Assessing candidate industrial technologies utilising hierarchical fuzzy decision making systems

Author

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  • Ivan Vrana
  • Shady Aly

Abstract

The adoption of new industrial technology is a type of critical decisions. Important characteristics of such significant decision problem are ill-structuredness, subjectivity and vagueness of input and output factors and their relationships. Most of past researches have considered only the quantitative view, and little or even no researches have treated inherent ambiguity in determining exact values of quantitative inputs and in quantifying subjective ones. In this paper, a hierarchical fuzzy decision making model is proposed for handling vagueness and subjectivity associated with the problem's inputs (i.e. technology performance factors), and for structuring the relationships between them at one side and a technology evaluation score at the other side. The inputs to the model are groups of technical, economical and transferability-related measures. The output of the model is a crisp score for comparing merits of candidate technologies. Finally, a hypothetical illustrative example is provided.

Suggested Citation

  • Ivan Vrana & Shady Aly, 2010. "Assessing candidate industrial technologies utilising hierarchical fuzzy decision making systems," International Journal of Industrial and Systems Engineering, Inderscience Enterprises Ltd, vol. 6(2), pages 187-206.
    • Handle: RePEc:ids:ijisen:v:6:y:2010:i:2:p:187-206
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