Fakülteler / Faculties

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    Optimization Of Drilling Process Parameters For Additive Manufacturing Parts Produced Using The Fdm Method
    (JOURNAL OF THE FACULTY OF ENGINEERING AND ARCHITECTURE OF GAZI UNIVERSITY, 2024-09-15) Zorer, Ezgi Selen; Ayhan, Emre; Yurdakul, Mustafa; Ic, Yusuf Tansel
    The melt deposition modeling method (FDM) is one of the increasingly widespread additive manufacturing methods, known as 3D printing, based on the layered assembly of material filaments. However, it is seen that the parts produced with FDM in the aviation industry do not have the desired dimensional and geometric tolerance values. For this reason, different manufacturing methods are used to bring the parts produced by the FDM method to the desired tolerance values. In this study, experiments were carried out to improve the tolerance values of the holes on the plates made of polycarbonate material, which is widely used in prototyping and production tools (welding, drilling, fixing) with FDM, and the optimum processing parameters were determined using the integrated design of experiment and TOPSIS methods. According to the obtained results, the optimum drilling parameters for the plate without pre-drilling case could be obtained by selecting HSS as the drill material, using cutting fluid, and setting the feed rate to 390.9091 mm/min and the spindle speed to 1000 rpm. For the pre-drilled plate, the optimum drilling parameters were again obtained by selecting the drill material HSS, using cutting fluid and applying the feed rate to 369.6970 mm/min and the spindle speed to 781.8182 rpm.
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    Development of A Financial Performance Benchmarking Model for Corporate Firms
    (2015) Ic, Yusuf Tansel; Tekin, Muhtesem; Pamukoglu, Fazil Ziya; Yildirim, S. Erdinc; 0000-0001-9274-7467; AGE-3003-2022; AGQ-5008-2022; AAI-1081-2020
    In this study, we developed a financial performance evaluation model to rank the corporate firms of 24 sectors in the Turkish economy. The developed model is based on the financial ratiosand Technique for Order Preference by Similiarity to Ideal Solution (TOPSIS) approach. This model of ferscorporate firm's rating scores with respect to its competitors belonging to the same industry. The developed model is coded in Visual Basic and tested with real case studies. Financial performance evaluation rankings obtained from TOPSIS, Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR), Grey Relational Grade (GRA), and Multi-Objective Optimization on thebasis of Ratio Analysis (MOORA) methods were compared by using Spearman's rank correlation test. Based on the test results, it was found that the TOPSIS method is the most appropriate method for the evaluation of financial performance. An application is also provided in the paper for illustrative purposes.
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    A TOPSIS Based Design of Experiment Approach to Assess Company Ranking
    (2014) Ic, Yusuf Tansel; https://orcid.org/0000-0001-9274-7467; AGE-3003-2022
    Company ranking is a complex process in which multiple financial ratios are required to be considered simultaneously. Furthermore, the selection process of an appropriate credit applicant company has become more complex as the experts in the financial organizations have to assess a wide range of alternatives based on a set of conflicting financial criteria. This paper studies the application of a new approach, i.e., Design of Experiment and TOPSIS method (DoE-TOPSIS) together to make company raking as frequently encountered in the real-time financial environment. The developed model is tested by case studies and satisfactory results are obtained. In the case studies, the results obtained by using the combined DoE-TOPSIS method are almost corroborated by those derived from conventional multi attribute decision making (MADM) methods which prove the applicability, potentiality, simplicity and flexibility of this method in making company ranking. (C) 2013 Elsevier Inc. All rights reserved.
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    Multi-response Simulation Optimization Approach for The Performance Optimization of An Alarm Monitoring Center
    (2014) Simsek, Baris; Ic, Yusuf Tansel; https://orcid.org/0000-0001-9274-7467; AGE-3003-2022
    This study offers a multi-response simulation-optimization approach to optimize an Alarm Monitoring Center's performance. In this paper, the multi-response simulation-optimization application is firstly addressed in the Alarm Monitoring Center. Five performance criteria affect the performance of Alarm Monitoring Center and five factors, each of which has three control levels, are identified. The data belonging to the performance criteria, which are determined, are obtained with the help of the running scenarios combining with the factor levels using Taguchi design. Then, signals to the noise (S/N) ratios are calculated for these which are obtained from the performance data. A decision matrix is generated with S/N ratios; the TOPSIS method is used to transfer the multi-response problems into the single-response problems. The system improvement rate is also determined by finding the levels of factors to optimize the system using Taguchi's single response optimization methodology.(C) 2014 Elsevier Ltd. All rights reserved.
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    Development of A New Multi-Criteria Optimization Method for Engineering Design Problems
    (2016) Ic, Yusuf Tansel; 0000-0001-9274-7467; AGE-3003-2022
    In this study, we developed a new multiple criteria optimization method in the context of engineering design. The design of experiment (DoE) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods are combined to identify an objective function of the selected problem by fitting a polynomial to the experimental data in a multiple linear regression analysis. Then, the regression function is incorporated into a mathematical model with the criteria constraints to determine an optimal criteria set. The proposed method can be used to compare the functionality and results provided by different scenario analyses of a building design optimization problem, which represent design solutions. We applied the DoE-TOPSIS model to solve different multi-criteria design optimization problems using two examples from the literature and obtained satisfactory results. In the examples, the results obtained using the combined DoE-TOPSIS model are almost in agreement with those derived from conventional multi-criteria design optimization methods, which demonstrates the simplicity, usability, and flexibility of the proposed method in solving engineering design problems.
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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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    Understanding the Effect of Assignment of Importance Scores of Evaluation Criteria Randomly in the Application of DOE-TOPSIS in Decision Making
    (2019) Ic, Yusuf Tansel; Yurdakul, Mustafa; 0000-0001-9274-7467; AGE-3003-2022
    In conventional applications of hybrid DoE-TOPSIS technique in decision making problems, full factorial design layouts are generally used because of their ability to measure the effects of all possible combinations for evaluation factors. In a typical application, for a design layout, a number of replications are generated by assigning different sets of relative importance scores for evaluation factors. A TOPSIS score is then obtained for each experiment and replication pair. Regression analysis is finally applied to obtain a relationship with inputs (values of evaluation factors) and outputs (alternatives' TOPSIS meta-model scores). The key in conventional application of hybrid DoE-TOPSIS technique is generation of relative importance scores. Each set of scores can be assigned by a decision maker or generated randomly. This paper aims to determine whether using either of the two methods in determination of relative importance scores makes any difference in the ranking orders of alternatives.
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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.
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    A knowledge-based material selection system for interactive pressure vessel design
    (2020) Yurdakul, Mustafa; Balci, Arif; Ic, Yusuf Tansel; AAI-1081-2020
    Continual introduction of new materials and improvements in existing materials increase the variety of materials that can be used for pressure vessel components. Among wide variety of materials, the most suitable one must be selected for a component by matching its functional requirements with various available materials' specifications. This study proposes an interactive knowledge-based decision support system for selecting the most suitable material for a given pressure vessel component and its working environment. The developed decision support system, namely Pressure Vessel SELection (PVSEL), consists of two separate phases. In the first elimination phase of PVSEL, the user obtains a feasible set of alternative materials by answering various questions and providing lower-limit values at materials' critical specifications. PVSEL, then, uses a ranking phase which uses ELECTRE, TOPSIS and VIKOR methods to rank the feasible materials. In the second phase, each alternative material's ranking is determined by combining its performance values at weighted critical specifications (selection criteria), which are considered as important in meeting the functional requirements of the component. Usage of PVSEL is illustrated in the paper and the results show that the proposed PVSEL is an effective selection tool and provides meaningful results for the designers.
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    Operating window perspective integrated TOPSIS approach for hybrid electrical automobile selection
    (2019) Ic, Yusuf Tansel; Simsek, Esra; AAI-1081-2020
    To reduce vehicle-related environmental pollution, environmental regulations should be taken into account in different levels of sustainable product development process. As a result of the increasingly emitted CO2 and serious energy shortage electrical or hybrid automobiles are one of the possible alternatives for customers. In this study, an operating window perspective based Taguchi-TOPSIS model is developed for the hybrid electrical automobile selection problem. Operating window is a range of attributes' values that the operating parameters meet the specified functional parameters yielding the best results in economic and technological terms. The operating window's upper and lower boundaries are defined as limits. More than two limit modes usually cannot be characterized by a one-dimensional operating window. After obtaining attribute values for the hybrid electrical automobile alternatives, the TOPSIS method is used for the ranking of the alternatives. The developed selection model is tested on a case study and satisfactory results are obtained.