An intelligent approach to machine tool selection through fuzzy analytic network process
| Autor: | Rifat Gürcan Özdemir, Zeki Ayağ |
|---|---|
| Přispěvatelé: | Ayaǧ, Zeki, TR141173, TR8785 |
| Rok vydání: | 2009 |
| Předmět: |
Engineering
business.product_category Analytic network process tezgah seçimi Analytic hierarchy process machine tool selection computer.software_genre multiple-criteria decision making (MCDM) Fuzzy logic Industrial and Manufacturing Engineering analytic network process (ANP) Artificial Intelligence ahp approach manufacturing systems Fuzzy number Analytic network process (ANP) decision-support-system ahp yaklaşım analitik ağ süreci (ANP) model business.industry bulanık mantık robot seçimi karar destek sistemi Vagueness robot selection Multiple-criteria decision making (MCDM) Machine tool Machine tool selection Ranking çevre Pairwise comparison fuzzy logic Data mining business environment computer çok kriterli karar verme (MCDM) Software imalat sistemleri |
| Zdroj: | Journal of Intelligent Manufacturing. 22:163-177 |
| ISSN: | 1572-8145 0956-5515 |
| DOI: | 10.1007/s10845-009-0269-7 |
| Popis: | In this study, we utilize analytic network process (ANP), a more general form of AHP, for justifying stand-alone machine tools out of available alternatives in market due to the fact that AHP cannot accommodate the variety of interactions, dependencies and feedback between higher and lower level elements. However, due to the vagueness and uncertainty on judgments of a decision-maker, the crisp pair wise comparison in the conventional ANP seems to be insufficient and imprecise to capture the right judgments of the decision-maker. That is why, also in this paper, fuzzy number logic is introduced in the pair wise comparison of ANP to make up for this deficiency in the ANP. In short, here, an intelligent approach to machine tool selection (MTS) problem through fuzzy ANP is proposed to improve the imprecise ranking of company's requirements which is based on the conventional ANP. In order to reach to final solution, a preference ratio (PR) analysis is done by using the results of the fuzzy ANP, and investment costs of alternatives. In addition, a numerical example is presented to illustrate the proposed approach. |
| Databáze: | OpenAIRE |
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