Mühendislik Fakültesi / Faculty of Engineering

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

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Author: search.filters.author.Ic, Yusuf TanselStart date: 2020

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Now showing 1 - 10 of 34
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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 Decision Support System for Selection of Reviewers to Evaluate Research and Development Projects
    (2023) Kocak, Serdar; Ic, Yusuf Tansel; Sert, Mustafa; Atalay, Kumru Didem; Dengiz, Berna
    The evaluation of Research and Development (R&D) projects consists of many steps depending on the government funding agencies and the support program. It is observed that the reviewer evaluation reports have a crucial impact on the support decisions of the projects. In this study, a decision support system (DSS), namely R&D Reviewer, is developed to help the decision-makers with the assignment of the appropriate reviewer to R&D project proposals. It is aimed to create an artificial intelligence-based decision support system that enables the classification of Turkish R&D projects with natural language processing (NLP) methods. Furthermore, we examine the reviewer ranking process by using fuzzy multi-criteria decision-making methods. The data in the database is processed primarily to classify the R&D projects and the word embedding model NLP, "Word2Vec". Also, we designed the Convolutional Neural Network (CNN) model to select the features by using the automatic feature learning approach. Moreover, we incorporate a new integrated hesitant fuzzy VIKOR and TOPSIS methodology into the developed DSS for the reviewer ranking process.
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    The Use of Petri Nets in Performance Analysis of Flexible Manufacturing Cell
    (2022) Bulca, Fatima Busra; Ic, Yusuf Tansel; Yurdakul, Mustafa
    A Flexible Manufacturing Cell (FMC) is a system that consists of computer-integrated machines, automatic material handling systems, and robots. It produces different part types with minimal worker involvement. Many different methods, such as queuing systems and simulation models, have been applied in FMC modeling in the literature. This study aims to use Petri Nets (PN) in modelling complex FMCs. The study is carried out in the FMC located in the Advanced Manufacturing Systems Laboratory of Baskent University. The FMC consists of a CNC machining center, a material handling robot and a pallet, which has three work-piece carriage capacities. Processing times of FMC elements may vary due to reasons (the power usage performance, air supply efficiency, electrical power efficiency, etc.) arising from the mechanical structure of the system. This uncertainty needs to be taken into account when modeling the system. In this study, the uncertain (fuzzy) processing times associated with the transitions were caused by the mechanical structure of the system. In order to compare with the newly developed fuzzy models, the system was first modeled using Transition Time Petri Nets (TTPN), in which the running times associated with the transition times take precise values. On the other hand, for handling fuzzy values of the actual operating times in the FMC, two models namely, Partial-Fuzzy Transition Time Petri Nets (Partial-FTTPN) and Fuzzy Transition Time Petri Nets (FTTPN) are developed. The results of the three models are compared to analyze the benefits of combining "time uncertainties" resulting from the natural behavior of FMCs.
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    A Forecasting Study for Renewable Energy Resources Investments in Turkey: TOPSIS-Based Linear Programming Model
    (2023) Oluklu, Dicle; Ic, Yusuf Tansel; 0000-0001-9274-7467
    In this paper, a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)-based linear programming (LP) approach is developed for determining optimal quantities of renewable energy sources according to the source's potential compared with other renewable energy alternatives. A combined model is established with the forecasting model, TOPSIS, and LP methods to determine optimal results. The developed decision support approach's applicability is illustrated in this paper. The paper illustrates how renewable energy sources can be preferred to meet additional energy demand in the next five years in Turkey using the developed TOPSIS integrated LP model. For this objective, a time series analysis is applied to estimate production capacity for the constraints of the mathematical model. Then, a question is answered how much energy should be produced from which alternative for each year? A flexible structured mathematical model is developed to meet the necessary energy requirements in dynamic and variable economic systems. So, the decision-maker can assign different criteria weights in the TOPSIS model, which is integrated with LP, and obtain new optimal solutions related to requirements in the future.
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    Analysis of the Robustness of the Operational Performance Using a Combined Model of the Design of Experiment and Goal Programming Approaches for a Flexible Manufacturing Cell
    (2023) Ic, Yusuf Tansel; Yurdakul, Mustafa; Dengiz, Berna; Sasmaz, Turgut
    A combined model of a 2(k) design of experiment (DOE) and goal programming (GP) approaches is presented to determine optimum levels of input variables and analyze their robustness for a multiobjective performance of a flexible manufacturing cell (FMC) in this study. Two main performance metrics, namely, manufacturing lead time (MLT) and surface roughness (SR), are considered performance outputs for the FMC. Machine sequence, robot speed, tool type, and material type are selected as the four input variables on the input side of the proposed model. The study shows that even with a limited number of experiments, one can determine optimum input levels for the multiobjective performance of the FMC and determine their robustness.
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    Development of a Goal Programming Model Based on Response Surface and Analytic Hierarchy Process Approaches for Laser Cutting Process Optimization of St-52 Steel Plates
    (2022) Yurdakul, Mustafa; Tukel, Taha; Ic, Yusuf Tansel
    This paper presents an integrated model for optimization of laser cutting process of St-52 steel plates with multiple performance characteristics using Goal Programming (GP), Analytic Hierarchy Process (AHP), and Response Surface Methodology (RSM) approaches. In this study, optimum levels of the laser cutting process input parameters namely, material thickness, cutting speed, laser power, and assist gas pressure are obtained. For optimization purposes, four different surface roughness types of a cut surface, surface hardness, cutting time, and heat-affected zone (HAZ) of the cut surface are considered as performance outputs (responses) in this study. Optimization of multiple performance objectives (responses) requires obtaining regression functions with RSM first, and then weighting the regression functions using the AHP and finally combining the multiple functions into a single overall goal within a GP model and solving the model to optimize the laser cutting process. The study clearly shows that the presented optimization model is flexible enough to optimize the laser cutting process for various scenarios and conflicting priorities.
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    A Simplified Throughput Model for a Unit-Load AS/RS Considering Dynamics Principles
    (2022) Ic, Yusuf Tansel
    This paper presents a unit-load automated storage and retrieval system's (AS/RS) throughput analysis that uses an S/R machine for diagonal aisle transportation and a structure for both vertical and horizontal transportations. Although many methods are available to compute the AS/RS throughput rate, the method recommended by the Material Handling Institute (MHI) is more suitable for real or practical cases. This method assumes (i) randomized storage with constant vertical and horizontal speeds of the S/R machine, and (ii) simultaneous travel in both directions. We consider a new simplified and more efficient approach for MHI's method to predict the throughput performance of the AS/RS.