Fuzzy analytic hierarchy process based group decision support system to select and evaluate new manufacturing technologies

Manufacturing organizations often make complex decisions in regards to investment in new manufacturing technologies (NMT). These NMT are assessed based on attributes such as flexibility, quality etc., which are hard to quantify. This fact calls upon the need for a structured decision support systems that can adequately represent qualitative and subjective assessments. The gist of this paper is to propose an integrated fuzzy analytic hierarchy process (AHP) based approach to facilitate the selection and evaluation of NMT in the presence of intangible attributes and uncertainty. Three important issues that are pertinent and critical to fuzzy AHP, namely contradiction in user preferences, deriving priorities from inconsistent fuzzy judgment matrices, and group decision-making are addressed in detail. Also, an attempt is made to compare fuzzy preference programming (FPP) and two-stage logarithmic goal programming (TLGP) based fuzzy prioritization methods. Based on the comparative study, it is concluded that FPP is preferred over TLGP to select and evaluate NMT. Numerical examples are provided to illustrate the aforementioned issues.