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Issue title: Special section: Decision Making Using Intelligent and Fuzzy Techniques
Guest editors: Cengiz Kahraman
Article type: Research Article
Authors: Aktas, Ahmeta; * | Aydin, Serhatb | Kabak, Mehmeta
Affiliations: [a] Department of Industrial Engineering, Gazi University, Ankara, Turkey | [b] Department of Industrial Engineering, Air Force Academy, National Defence University, Istanbul, Turkey
Correspondence: [*] Corresponding author. Ahmet Aktas, Department of Industrial Engineering, Gazi University, 06570, Ankara, Turkey. E-mail: aaktas@gazi.edu.tr.
Abstract: To cut several types of hard materials in manufacturing, Computer Numeric Control (CNC) router machines are commonly used. The tasks to be done by different machines can be performed by a single CNC router machine. Production of parts with better quality is possible at lower costs by production with CNC router machines, and these machines improve the productivity of manufacturing system. For these reasons, determination of the appropriate CNC router machine for manufacturing systems is a crucial decision. Different factors related to properties of machines are effective on the decision. Therefore, decision makers must include different effective aspects into decision process. Under this consideration, an analytic selection procedure for CNC router machines by taking uncertain expressions of experts on the selection criteria and variable values occur over time is proposed in this study. In order to handle the modelling difficulty of uncertainty of the statements and the value changes by time, dynamic intuitionistic multi attribute decision making is used to select the best CNC router. Applicability of the proposed selection procedure is demonstrated on an application, and a comparative analysis with dynamic neutrosophic multi attribute decision making is presented.
Keywords: Dynamic decision making, intuitionistic fuzzy sets, neutrosophic sets, multi attribute decision making, CNC router selection
DOI: 10.3233/JIFS-189094
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 6259-6269, 2020
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