Mühendislik Fakültesi / Faculty of Engineering

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

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    A Robust Aluminum Material Selection Process in the Aviation Industry: A Linear Discrete System Stability Test Perspective for Fuzzy Multicriteria Decision-Making
    (Başkent Üniversitesi Mühendislik Fakültesi, 2024-04-10) Ic, Yusuf Tansel; Hamzaoglu, Burak Meric; Yurdakul, Mustafa
    Aluminum parts are used in the aviation industry because of the need for light. However, in addition to lightness, critical parts that must have high strength properties have also been developed. The corrosion resistance, resistance to high temperatures, and workability were investigated in this case. It becomes difficult to choose among many aluminum materials that can be alternatives to each other when these features are included. The developed approach, which considers many of the features listed above and ultimately recommends to the user the most suitable aluminum material for the relevant critical part, will be used in overcoming the difficulties in this process. A material selection model is proposed in this paper for this purpose, and the decision-making model is demonstrated with examples from the aviation industry. Therefore, the developed model, which will enable the selection of the most suitable materials among alternative materials, especially for critical parts in the aviation industry, will guide professionals working in this field. For this purpose, the fuzzy TOPSIS method is used in the study, and suitable alternatives are determined. Finally, a robustness analysis is proposed to determine the most suitable aluminum material for highly uncertain situations. We apply a stability evaluation study based on process control theory in the robustness analysis.
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    A Fuzzy Computing Approach To Aggregate Expert Opinions Using Parabolic And Exparabolic Approximation Procedures For Solving Multi-Criteria Group Decision-Making Problems
    (Başkent Üniversitesi Mühendislik Fakültesi, 2024-03-02) Ic, Yusuf Tansel
    Triangular fuzzy numbers (TFNs) are widely used for selection problems to determine expert opinions using linguistic expressions. Some aggregation procedures are developed to determine expert opinions more accurately. However, there is a need for a simple and more useful procedure to solve the selection problems more suitably. For this purpose, our study offers a triangular, exparabolic, and parabolic area calculation-based approximation approach for TFNs to aggregate the possible hedges (very and more or less) for TFNs. Hence, this aggregation procedure provides a tuning opportunity for classical TFN expressions to capture possible tuning processes to reflect the hesitancies of experts. The technique for order preferences by similarity to ideal solution (TOPSIS) method is applied in the two studies from extant literature, and suitable alternatives are determined as a result of the ranking process. Finally, a comparative analysis is presented to illustrate the efficiency of the proposed procedure. The conventional TOPSIS model's ranking scores are very close for exemplified examples (i.e., 0.5308, 0.4510, 0.4550 and 0.5304, 0.4626, 0.4940), but the proposed model's result has fluctuated for the same examples (i.e., 0.346, 0,669, 0,567 and 0.208, 0.991, 0.148). So, the main advantage of the proposed aggregation procedure is the alternative ranking scores separation capability analyzed with their linguistic diversification.
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    Improving The Quality Of Micro Holes Drilled With A Current Detection Plasma Arc Device
    (JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING, 2024-10) Ic, Yusuf Tansel; Kocum, Cengiz; Atalay, Kumru Didem; Serdaroglu, Dilek Cokeliler; Akar, Gurel; Polat, Isil Yanki; Samsun, Berk; Caliskan, Sevde; Atmaca, Dicle Naz; Karayalcin, Serkan
    Today, microholes play a crucial role in many sectors. Microholes are used in fields such as aerospace, computer systems, and electronic and mechanical industries. In this paper, we improve the performance of the current sensing plasma arc device to create holes within the same diameter, appropriate delamination, and surface quality. In addition, we aim to improve the processing quality of the current sensing plasma arc device, which drills holes from the micron level to the millimeter level and creates microstructures on hard, durable, and inert materials such as glass and quartz. Additionally, we presented a multiobjective optimization model to reach the optimal factor levels to obtain the minimum hole diameter with minimum delamination. For this objective, we propose a design of an experiment-integrated goal programming model in this study. The optimal levels are 90 Watt, 18 Hz, 2.73 ms, and 11.6 cm for the parameter values Power, Frequency, Lead time, and Distance between the probes, respectively, to reach the optimal diameter (183 mu m) and delamination values (1.025).
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    A Dss Development Study For Document Distribution Networks For Preparing Autonomous Vehicle-Integrated Distribution Systems
    (DECISION, 2024-12) Derya, Tusan; Ic, Yusuf Tansel; Erbay, Mehmet Dogan; Konuk, Kubra; Fidan, Nihal
    We propose a decision support system (DSS) to complete the tours of the routes of the traveler in charge of document distribution in the least amount of time for the document distribution task of a university to prepare autonomous vehicle-integrated distribution systems. A mathematical model-based decision support system is developed to determine distribution routes that optimize the total distance to target locations and obtain optimal system conditions for use in the migration of autonomous distribution systems. The purpose is to find the shortest-cost tours to cover all or subsets of edges in a network. Documents are shared and distributed by travelers to other related locations. Soon after, travelers will be replaced by autonomous vehicles. There are many application areas, such as newspapers and mail delivery systems. Therefore, the proposed model can be easily extended to other application areas, such as newspaper, cargo, and mail delivery systems, to construct autonomous vehicle-based systems.
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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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    The New Fuzzy Bottleneck Model to Improve The Axle Manufacturing System Performance
    (INTERNATIONAL JOURNAL OF INTERACTIVE DESIGN AND MANUFACTURING - IJIDEM, 2024) Sari, Haci; Ic, Yusuf Tansel
    Axles are the crucial undercarriage part of vehicles and affect the total number of manufactured vehicles. Therefore, they are essential parts since they directly affect the production quantity. Some uncertainties arise in the lead times of the machining process in the manufacturing system due to the variability in factors, such as human, machine, and material properties. In this study, the efficiency of the axle manufacturing process is investigated, and performance in the machining unit of an automotive spare part manufacturer company is improved. This study aims to increase the production capacity of the company by using a fuzzy logic-based bottleneck analysis. In this study, a new model is proposed by integrating fuzzy logic the Solberg's bottleneck model, and the performance of the manufacturing system is improved by applying the developed model in the machining unit of the company. At the end of the study, the increase in production rate and the benefit to the company is obtained.
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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 Decision Support System for Selection of Net-Shape Primary Manufacturing Processes
    (2014) Yurdakul, Mustafa; Arslan, Emre; Ic, Yusuf Tansel; Turkbas, O. Selim; https://orcid.org/0000-0001-9274-7467; AGE-3003-2022
    Developments in the capabilities of the manufacturing processes increased the number of processes that can produce a part within the requirements determined by its design and market research. The increased number of processes and unfamiliarity of manufacturing engineers to many new manufacturing processes forces the researchers to develop systematic process selection tools instead of depending on the accumulated human expertise only. In this paper, a net-shape primary manufacturing process selection decision support system (DSS), which is named PROSEL (PROcess SELection), is developed. The developed selection programme eliminates the unsuitable processes step by step by checking a part's material, annual production quantity, specified shape, thickness and presents the most economical process as the most appropriate net-shape primary process after a final cost analysis. The developed DSS is written in Visual Studio and tested with a great deal of real-life examples. It can be concluded from the tests that the programme provides the same or better primary manufacturing process selection decisions than the practical usage, and it is a very useful support tool for net-shape primary process selections.
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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.