The application of fuzzy Delphi and fuzzy inference system in supplier ranking and selection

In today’s highly rival market, an effectivesupplier selection process is vital to the success of anymanufacturing system. Selecting the appropriate supplier isalways a difficult task because suppliers posses variedstrengths and weaknesses that necessitate careful evaluationsprior to suppliers’ ranking. This is a complex processwith many subjective and objective factors to considerbefore the benefits of supplier selection are achieved. Thispaper identifies six extremely critical criteria and thirteensub-criteria based on the literature. A new methodologyemploying those criteria and sub-criteria is proposed for theassessment and ranking of a given set of suppliers. To handlethe subjectivity of the decision maker’s assessment, anintegration of fuzzy Delphi with fuzzy inference system hasbeen applied and a new ranking method is proposed forsupplier selection problem. This supplier selection modelenables decision makers to rank the suppliers based on threeclassifications including ‘‘extremely preferred’’, ‘‘moderatelypreferred’’, and ‘‘weakly preferred’’. In addition, ineach classification, suppliers are put in order from highestfinal score to the lowest. Finally, the methodology is verifiedand validated through an example of a numerical test bed.