Browsing by Author "Unver,H.O."
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Conference Object Citation Count: 2Evaluation of partner companies based on fuzzy inference system for establishing virtual enterprise consortium(Springer Verlag, 2015) Kılıç, Sadık Engin; LotfiSadigh,B.; Ozbayoglu,A.M.; Unver,H.O.; Kilic,S.E.; Manufacturing EngineeringVirtual Enterprise (VE) is one of the growing trends in agile manufacturing concepts. Under this platform companies with different skills and core competences are cooperate with each other in order to accomplish a manufacturing goal. Success of VE, as a consortium, highly depends on the success of its partners. So it is very important to choose the most appropriate companies to enroll in VE. In this study a Fuzzy Inference System (FIS) based approach is developed to evaluate and select the potential enterprises. The evaluation is conducted based on four main criteria; unit price, delivery time, quality and past performance. These criteria are considered as inputs of FIS and specific membership functions are designed for each. By applying fuzzy rules the output of the model, partnership chance, is calculated. In the end, the trustworthy of the model is tested and verified by comparing it with fuzzy-TOPSIS technique providing a sample. © Springer International Publishing Switzerland 2015.Conference Object Citation Count: 0Partner selection in formation of virtual enterprises using fuzzy logic(SciTePress, 2015) Kılıç, Sadık Engin; Sadigh,B.L.; Ozbayoglu,A.M.; Unver,H.O.; Kilic,S.E.; Manufacturing EngineeringVirtual Enterprise (VE) is a temporary cooperation among independent enterprises to build up a dynamic collaboration framework for manufacturing. One of the most important steps to construct a successful VE is to select the most qualified partners to take role in the project. This paper is a survey of ranking the volunteer companies with respect to four evaluation criteria, proposed unit price, delivery time, quality and enterprises' past performance. Fuzzy logic method is proposed to deal with these four conflicting criteria, considered as input variables of the model. As each criterion is different in nature with the other criterion, various membership functions are used to fuzzify the input values. The next step is to construct the logical fuzzy rules combining the inputs to conclude the output. Mamdani's approach is adopted to evaluate the output in this Fuzzy Inference System. The result of the model is the partnership chance of each partner to participate in VE. A partner with highest partnership chance will be the winner of the negotiation. Implementation of this model to the illustrative example of a partner selection problem in virtual enterprise and comparing it with fuzzy-TOPSIS approach verifies the feasibility of the proposed approach and the computational results are satisfactory. Copyright © 2015 SCITEPRESS - Science and Technology Publications All rights reserve.