Mühendislik Fakültesi / Faculty of Engineering

Permanent URI for this collectionhttps://hdl.handle.net/11727/1401

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search.filters.applied.f.publicationcategory: search.filters.publicationcategory.Makale - Ulusal Hakemli DergiSubject: search.filters.subject.multi-criteria decision making

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    Development of a multi-criteria decision making model for the selection of appropriate robots for the aerospace industry
    (2021) Celek, Osman Emre; Yurdakul, Mustafa; İç, Yusuf Tansel
    Industrial robots have different capabilities and features according to their application areas and requirements. In a sector with highly specialized processes such as aerospace industry, accurate selection of an industrial robot to meet the requirements is a very complex and difficult process. The main challenge is that there are many appropriate robots for the aircraft manufacturing and assembly processes. In addition many technical criteria should be evaluated for determining the most appropriate robot among the industrial robots. In this study the MOORA and TOPSIS method, which are multi-criteria decision making methods are presented for the selection of appropriate industrial robots in the aerospace industry. A real case study related to the application of the methods is also included in the paper content.
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    Analysis of the effect of the number of criteria and alternatives on the ranking results in applications of the multi criteria decision making approaches in machining center selection problems
    (2020) Ic, Yusuf Tansel; Yurdakul, Mustafa
    Multi criteria machining center selection models are widely used in the literature. In the applications of multi-criteria decision making models, machining center selection criteria are directly taken from catalogues. It is known that to have a ranking model sensitive to the weights of the selection criteria, it is especially important to limit the number of selection criteria to 7 +/- 2. A similar proposal can be put forward for the number of machining centers. In this study, whether or not reducing the number of criteria and alternative machining centers make the ranking results more sensitive to the changes in the criteria weights is studied using Spearman's rank correlation test. The study results show that the ranking results become more sensitive with a reduced number of criteria and alternative machining centers.