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

In today's highly rival market, an effective supplier selection process is vital to the success of any manufacturing system. Selecting the appropriate supplier is always a difficult task because suppliers posses varied strengths and weaknesses that necessitate careful evaluations prior to suppl...

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Bibliographic Details
Published in:Journal of industrial engineering international 2014-09, Vol.10 (3), p.1-16, Article 66
Main Authors: Tahriri, Farzad, Mousavi, Maryam, Haghighi, Siamak Hozhabri, Dawal, Siti Zawiah Md
Format: Article
Language:English
Subjects:
Component and supplier management
Criteria
Decision making
Engineering
Engineering Economics
Facility Management
Fuzzy Delphi method
Fuzzy inference system
Fuzzy systems
Industrial and Production Engineering
Inference
Logistics
Marketing
Mathematical and Computational Engineering
Multiple-inputs multiple-output
Organization
Original Research
Quality Control
Ranking
Reliability
Safety and Risk
Supplier selection
Suppliers
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Summary:In today's highly rival market, an effective supplier selection process is vital to the success of any manufacturing system. Selecting the appropriate supplier is always a difficult task because suppliers posses varied strengths and weaknesses that necessitate careful evaluations prior to suppliers' ranking. This is a complex process with many subjective and objective factors to consider before the benefits of supplier selection are achieved. This paper identifies six extremely critical criteria and thirteen sub-criteria based on the literature. A new methodology employing those criteria and sub-criteria is proposed for the assessment and ranking of a given set of suppliers. To handle the subjectivity of the decision maker's assessment, an integration of fuzzy Delphi with fuzzy inference system has been applied and a new ranking method is proposed for supplier selection problem. This supplier selection model enables decision makers to rank the suppliers based on three classifications including ''extremely preferred'', ''moderately preferred'', and ''weakly preferred''. In addition, in each classification, suppliers are put in order from highest final score to the lowest. Finally, the methodology is verified and validated through an example of a numerical test bed.
ISSN:2251-712X
1735-5702
2251-712X
DOI:10.1007/s40092-014-0066-6