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    APPLYING EDAS AS AN APPLICABLE MCDM METHOD FOR INDUSTRIAL ROBOT SELECTION
    (Yildiz Technical University, 2019) Yalçin, Neşe; Uncu, Nuşin
    In order to stay an actual competitor in today’s environment, it is essential for manufacturing organizations to make decisions promptly and correctly. In the real-time manufacturing decision making problems, some alternatives are more likely to be evaluated with respect to multiple conflicting criteria. Several multi-criteria decision-making (MCDM) methods have been available to help decision makers in choosing the best decisive course of actions. The aim of the study is to apply an efficient and relatively new method called Evaluation based on Distance from Average Solution (EDAS) as an applicable and useful MCDM method for robot selection problem (RSP). In order to examine the feasibility and effectiveness of the presented method, several numerical examples from the literature are considered. Comparing with other methods especially MCDM methods given in the literature for the industrial RSPs, the Spearman’s rank correlations analysis indicates that this method is capable of accurately ranking selected robots. © 2019 Yildiz Technical University. All Rights Reserved.
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    Distance restricted maximal covering model for pharmacy duty scheduling problem
    (Balikesir University, 2018) Uncu, Nuşin; Bulğurcu, Berna; Kılıç, Fatih
    Pharmacies are considered as an integral part of health care systems for supplying medicine to patients. In order to access medicine with ease, pharmacies locations in the context of distance and demand are important for patients. In the case of a few numbers of pharmacies may be on duty at nights or during holidays, pharmacies duty scheduling problem occur and can be associated with location models. In contrast to widely used p-median model which aims to minimize the demand-weighted distance, we maximize the demand covered over the distance between the patients and the pharmacies on duty. Main contribution of the proposed model is the restriction constraint for the distance between pharmacies on duty in order to ensure fairness in an organizational view of point. We propose a distance restricted maximal covering location model (DR-MCLM) in this study. This mathematical model is a mixed integer linear programming model and solved by Lingo optimization software. The distances between the pharmacies and the sites are obtained using Geographic Information Systems (GIS). The model is applied for the case in Adana, one of the biggest cities in Turkey. The results are given on the maps of the city, including the pharmacies on duty and their assignments to sites in each day of the period. © 2018 Balikesir University. All rights reserved.
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    Evaluating the Performance of Railway Transportation Companies Using Multi-Criteria Decision-Making Methods
    (2024) Yüksel, Çağdaş; Uncu, Nuşin
    The purpose of performance evaluation is to generate measurable data on an organization's performance, with the goal of assisting managerial decision-making and enhancing overall performance. In this study, the key performance indicators (KPIs) for railway transportation companies are identified based on expert opinions and previous frameworks. The operational performance of various railway freight transport companies was evaluated using multi-criteria decision-making methods (MCDM). Among the MCDM approaches, the Evaluation Based on Distance from Average Solution (EDAS) method was applied as the main method. In addition to the EDAS method, alternative MCDM methods such as TOPSIS, PROMETHEE II, and COPRAS were used to highlight potential deviations when compared to the results obtained with the EDAS method. Based on the research findings, three out of the seven KPIs, namely safety, have the highest weight at 38%, followed by punctuality at 19%, and journey time at 12%. Subsequently, companies were ranked according to their performance based on all KPIs. Furthermore, a sensitivity analysis was conducted to demonstrate how changes in the relative weights of KPIs can affect the results.
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    EVENT DATA VISUALIZATION THROUGH PROCESS MINING:A CASE FOR EMERGENCY MEDICAL SERVICE SYSTEM IN ADANA
    (2019) Uncu, Nuşin
    Increasing amount of data enables researchers the opportunity of applyingnew scientific methods to manage and visualize the systems and processes.Process mining is an emerging tool for discovering real processes using eventdata of complex systems such as communication, information, health caresystems, transportation and etc. Emergency Medical Service (EMS) system isan integral part of health care systems and aims to respond cases on time inorder to decrease mortality. Although the EMS system process is assumed tobe known, related data may indicate some deviations from the real process.Aim of this study is to discover and visualize EMS system in Adana city, inTurkey. EMS system event logs are filtered and visualized by using plug-insin ProM platform such as Simple Heuristic Filtering plug-in and Logvisualizer, respectively. Other plug-ins such as Fuzzy Miner and InductiveMiner are used for discovering process model. The deviations are obtained inEMS system process model showing irregular or rare events that cannot berepresentable throughout the process. The results indicate that the process oftransportation between hospitals should be investigated in order to improvethe process of Adana EMS system.
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    FMEA Based Fuzzy Topsis for Assessment of Quality Problems in Telescopic Platform Production
    (2022) Bocut, Mahire Seray; Uncu, Nuşin
    In order to increase process and product quality fast and least costly, it is very useful to focus on the process that causes the important quality problems. In this study, quality problems and related processes in a company that produces on-vehicle equipment in the automotive industry are examined. The purpose of this study is to provide a quality improvement perspective to reduce process and product defects. Fault Mode and Effects Analysis (FMEA) is applied to detect faults, determine their causes and prioritize them. Prioritization of critical quality errors is revealed using traditional FMEA and FMEA-based fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The FMEA-based fuzzy TOPSIS method has been proposed because of its ability to handle uncertainty arising from the subjective judgments of decision makers. The results are compared and the preventions are suggested to avoid from the most important process that causes the quality problem.
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    Isınma Periyodu Belirleme Yöntemlerinin Etkinliklerinin Analizi
    (2017) Uncu, Nuşin
    Kesikli olay simülasyonunda, performans çıktı değerlerinin yansız tahmini için sistemi başlangıç durumu etkilerinden arındırmak gerekmektedir. Özellikle sonlanmayan modellerde, sistemin durağan duruma ulaşana kadar geçirdiği süre yani ısınma periyodu istatistikleri, performans çıktı değerlerinin üzerindeki yanlı etkilerinin ortadan kaldırılması için hesaplamalara dâhil edilmemelidir. Simülasyon ve optimizasyon yöntemlerinin birlikte kullanıldığı problemlerde ise simülasyon parametrelerinin her koşum öncesi güncellenmesi ısınma periyodunda da değişimlere sebep olmaktadır. Bu değişimi azaltmak için, anlık ısınma periyodu belirleme yöntemleri kullanılmaktadır. Bu çalışmada, Welch Grafik yöntemi ve anlık ısınma periyodu belirleme yöntemlerinden Üstel Değişim Oranı Kuralı ve Öklid Uzaklığı yöntemleri M/M/1 kuyruk modeli için uygulanmıştır. Yöntemler etkinlikleri analitik sonuçlara yakınsama başarımları ve CPU zamanları bazında etkinlikleri karşılaştırılmıştır