Scopus İndeksli Açık & Kapalı Erişimli Yayınlar

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Author: search.filters.author.Dengiz, BernaSubject: search.filters.subject.TOPSIS

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    Analysis of the manufacturing flexibility parameters with effective performance metrics: a new interactive approach based on modified TOPSIS-Taguchi method
    (2022) Ic, Yusuf Tansel; Sasmaz, Turgut; Yurdakul, Mustafa; Dengiz, Berna; 0000-0001-9274-7467; AGE-3003-2022
    Flexibility is one of the most important strategy parameters to achieve a long-term successful performance for a manufacturing company. Studies in the literature aim to operate a manufacturing system at optimum levels of flexibility parameters under its own manufacturing environment. This study aims to present an interactive analysis framework based on TOPSIS and Taguchi parameter design principles for investigating the effects of different levels of flexibility parameters on the performance of a flexible manufacturing cell (FMC). The main performance metric used in this study is manufacturing lead time. Other important metrics to evaluate quality control and inspection policies are also investigated in this study. To conclude, a combined model of an interactive approach based on TOPSIS and Taguchi methods are used to assess the effectiveness of the flexibility parameters for a FMC.
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    The development of a reviewer selection method: a multi-level hesitant fuzzy VIKOR and TOPSIS approaches
    (2021) Kocak, Serdar; Ic, Yusuf Tansel; Atalay, Kumru Didem; Sert, Mustafa; Dengiz, Berna; 0000-0001-9274-7467; AGE-3003-2022
    This paper proposes a new approach for the selection of reviewers to evaluate research and development (R&D) projects using a new integrated hesitant fuzzy VIKOR and TOPSIS methodology. A reviewer selection model must have a multi-level framework in which reviewer selection strategies and related objectives guide the second level of the reviewer performance ranking process. The model must measure reviewer performance related to the activities that are necessary for the R&D project evaluation to be successful. A novel model is presented in this paper. In the proposed methodology, the aim is to select a reviewer in a hierarchical decision-making structure. The selection criteria values and their weights were obtained using the hesitant fuzzy VIKOR method. For the selection of a suitable reviewer, the conventional TOPSIS model was used. We developed a simpler procedure for effectively performing the reviewer selection process. The new approach was tested with a real case study and satisfactory results were obtained. A comparative analysis is also included in the article for illustrative purposes.