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Now showing 1 - 10 of 26
  • Publication
    Team planning under an electricity failure for a GSM operator
    (2019) Çakır, Kübra; Yılmaz, Nur; Bayrak, Meltem; YÜKSEKTEPE, FADİME ÜNEY
    Base stations are very important for all GSM operators. Efficient base stations prevent income loss while bringing prestige to the company. This study deals with the problem of transportation planning of portable generators during electricity failure for a leading Turkish GSM operator. There are often electricity failures in a particular area of Mersin which cause not only customer complaints but also income loss for the company. After an electricity failure, a battery steps in for that station. However, the lifetime of battery is limited and sometimes not enough during the failure. In that case, a fixed generator could step in to give service properly. Unfortunately, because of the high cost of fixed generators, not all base stations have a fixed generator. Therefore, the company tries to interfere this problem by using limited number of portable generators. Field operation teams transport and set up these portable generators to the sites with electricity failure before the battery dies. The problem is to schedule the transportation of portable generators to the base stations with electricity failure. In this study, composite dispatching rule, one of the scheduling algorithms, is used to solve this planning problem effectively. An Excel based decision support system has been developed for field operation team. Whenever a failure occurs, after inputting necessary information to the Excel, transportation schedule for each team could be easily obtained by the company experts.
  • Publication
    Industry 4.0 Scorecard for SMEs
    (Springer, 2018-09) Gergin, Zeynep; Gençyılmaz, Mehmet Güney; İlhan, Doğan Aybars; Dündar, Uğurcan; Cebeci, Özay; Çavdarlı, Ali İhsan; YÜKSEKTEPE, FADİME ÜNEY; AKTİN, AYŞE TÜLİN; 141772; 30141; 109203; 274545; 275477
    Today the industry is revolutionizing into a new era with the total integration of all elements of the production through digitalization and establishing communication between each other. This new revolution is named as “Industry 4.0”. Turkey is categorized as a developing country in terms of economy and Turkish economy is ranked at 17th place in world Gross Domestic Product (GDP) ranking. The country’s economy met the expectations and reached 7.4% GDP growth in 2017 while worldwide average growth was 3.6%, and developing countries had the average of 4.6%. Turkish government encourages enterprises to keep up with industry 4.0, and KOSGEB (Small and Medium Sized Enterprises Development Organization) is supporting the SMEs with various programs. This can be seen as an opportunity for Turkish industry to catch the trend and increase its growth rapidly. And at this point the exact knowledge of the current situation is crucial. Small and Medium Sized Enter- prises (SME) has the 99.8% of the total according to Turkish Statistical Institute (TÜİK). Hence, this project is initiated to identify the current situation of SMEs of Turkish industry. A comprehensive questionnaire is prepared to find out the readiness and requirements of the SMEs for Industry 4.0 transformation. This questionnaire is applied to SMEs operating in Marmara Region of Turkey. The outcome of the research shows a scorecard for the SMEs in terms of technology usage, readiness to Industry 4.0, and also increased their awareness on the concept and the importance of the new era. The future studies are continuing as a second phase of this research in order widen the research to all regions of the country, and to develop the transformation capabilities of the selected enterprises.
  • Publication
    Bir ilaç Firmasında Hammadde Sipariş Miktarının ve Stok Seviyelerinin Optimizasyonu
    (2019-06) Bodur, Buket; Akman, Gökcan; Sönmez, Rojda Nisa; Altınyar, Aydan; YÜKSEKTEPE, FADİME ÜNEY; 108243
    Günümüzde küreselleşmeyle birlikte şirketler arasındaki rekabet artmakta olup, ilaç şirketleri artan talep ile daha fazla ürün üretme hedefli koymaya başlamaktadır. Son dönemdeki demografik yapının değişmesi, ortalama yaşam beklentisinin ve yenilikçi teknolojilerin kabulünün artmasına paralel olarak, sağlık ve ilaç harcamaları artmaktadır. Mustafa Nevzat İlaç Sanayii, 1090 personeliyle Türk ilaç sektörünün öncüsü olan modem tesisleri ile makrolid grubu aktif maddeleri ve etodolak ve diğer aktif maddeler gibi bağımsız dört ilaç grubunu üretmektedir. Firmanın yıllar içinde büyümesiyle beraber, mevcut stok kontrolleri, sipariş miktarları, maliyet hesaplamalarında optimizasyon anlamında bazı noktalarda zorluklar yaşamaktadır. Firmanın öncelikli hedefi, yıl içerisinde üretecekleri ürünlerin hammadde siparişlerindeki optimum miktarı belirleyip, stok kontrolünü yaparak bu kısımlardan doğan maliyeti en iyi seviyeye çekmektir. Bu projede, Mustafa Nevzat İlaç Sanayi şirketinin artan talep miktarı ile birlikte hammadde stok seviyesi optimizasyonu nu yaparak şirketin hammadde stok maliyetlerinin düşürülmesi hedeflenmiştir. Bu çalışmada, firma tarafından verilen hammaddeler için geçmiş yıla ait toplam tüketim miktarları, satın almak maliyetleri, sipariş verme maliyetleri ve stok taşıma maliyetleri gibi bilgiler toplanmıştır. Bu veriler kullanılarak, her bir hammadde için Ekonomik Sipariş Miktarı belirlenmiştir. Sonuçlar, geçen yıl firma tarafından uygulanmış olan mevcut durum ile kıyaslanmıştır. Ayrıca, firma yetkililerinin değişen veriler olduğu durumda daha sonraki dönemlerde de kullanabilmesi için Excel tabanlı bir karar destek sistemi geliştirilmiştir.
  • Publication
    Comparative Analysis of the Most Industrialized Cities in Turkey from the Perspective of Industry 4.0
    (2019-08) Gergin, Zeynep; ILHAN, DOGAN AYBARS; Gençyılmaz, M.Güneş; DÜNDAR, Uğurcan; Çavdarlı, Ali İhsan; YÜKSEKTEPE, FADİME ÜNEY; 141772; 274545; 30141; 275477
    It can be declared that the adaptation of companies to the new industrial revolution, so called Industry 4.0, is not a choice but an issue of survival. The structure of business processes are changing with the newly introduced, radical and highly value adding technological drivers, such as internet of things, cloud computing, autonomous robots, augmented reality, cyber security system, etc. In the globalized trade markets none of the companies can close their eyes to this new era and ignore the required change in their operations. Small and Medium Sized Enterprises (SMEs) have 99.8% enterprise share of Turkey, and consequently have obvious contribution not only to the local economy but also to the global competition strength of the country. In that sense, catching up the fourth industrial revolution has to be the prior agenda of the SMEs, and also of the government institutions and the universities from the perspective of giving the required support. This study is the continuum of the broad research that is initiated in March 2018. The purpose is to identify the current situation of SMEs in Turkey with respect to their various implementations for Industry 4.0 transformation. A specifically designed questionnaire is applied to SME’s with the support of KOSGEB (Small and Medium Sized Enterprises Development Organization), and in this stage of the research, the companies located in four major cities, namely Istanbul, Ankara, Izmir and Bursa, are analyzed and compared. The study aims to find out the level of awareness and readiness of SMEs in these cities and measure their Industry 4.0 scores. The final target is to support the Industry 4.0 implementations by defining the current situation and proposing suitable actions for adaptation based on varying results.
  • Publication
    Data Mining Based CustomerResponse Prediction for a Specific Campaign in Pent
    (2018-07) Aral, Neslişah; Mutlu, Merve; Çiçekli, Sevra; YÜKSEKTEPE, FADİME ÜNEY; 108243; 297802
    PENTİ was established in 1950 in Turkey. Il is growing in produc­tion and retail activities, expanding its offering of mainly women’s and girls' socks, home wear and beachwear. Different campaigns are or­ganized to increase sales and customers are informed about the cam­paigns mostly by SMS regardless of their previous purchasing behav­ior. However, there is not an analytical tool to determine which cus­tomers those SMS should be sent to in order to get a high number of responses. In this study, an analytical tool which will predict the possible re­sponses of customers to a specific campaign will be developed by using WEKA software. While developing this tool, attributes such as age, having child, marital status and city information of customers will be preprocessed to analyze which ones are distinguishing when determin­ing the final attribute which is the response of customers. Following that, several data classification algorithms will be applied and the one which has the best accuracy rate will be proposed to the company. By the help of this tool. SMSs can be sent to the customers considering those attributes and the company can reach right group of people who will do shopping at stores after those informative SMSs.
  • Publication
    E-Ticaret Müşteri Davranışını Tahmin Etmek İçin Bir Veri Madenciliği Yaklaşımı
    (2018-06) Altunan, Büşra; Arslan, Ebru Dilara; Seyis, Merve; YÜKSEKTEPE, FADİME ÜNEY; 108243
    1841 yılında kurulan Watsons, 11 farklı pazarda 6300'den fazla mağaza ile dünyanın önde gelen güzellik ve kişisel bakım endüstrilerinden biridir.280 Watsons mağazasına ek olarak, online alışveriş de Türk müşterileri için bir alternatiftir. Mevcut eğilimler nedeniyle, birçok müşteri online alışverişi tercih etmektedir. Müşterilerden bazıları, ürünlerini market sepetlerine eklemekte, ancak maalesef, satın almadan web sitesinden ayrılmaktadırlar. Bu durum, e-ticaret perakendecilerinin çoğu için önemli bir soruna neden olmaktadır. Bu projede, web sitesi ziyaretleri sırasında müşterinin davranışını tahmin etmek için bir veri madenciliği yaklaşımı gerçekleştirilecektir. İlk adımda, web sitesi müşterisinin belirli bir gün için demografik ve davranışsal verileri toplanacaktır. İkinci adımda, veriler ön işlemeden geçirilecek ve eksik değerler kontrol edilecektir. Bir müşterinin satın alıp almayacağını öngörmek için önemli özellikler belirledikten sonra, en doğru veri sınıflandırma yöntemi WEKA kullanılarak belirlenecektir. Web sitesini ziyaret eden müşterilerin alışveriş yapıp yapmama konusundaki eğilimini tahmin etmek için bir karar destek sistemi önerilecektir. Sonuç olarak, şirket müşterinin davranışını web sitesine ilk girişinde tahmin etmesine faydalı olacak bir yöntem önerilecektir.
  • Publication
    A mathematical programming approach to paired kidney exchange: the case of Turkey
    (2018-08) Akın, Barış; YÜKSEKTEPE, FADİME ÜNEY; AKTİN, AYŞE TÜLİN; GÜNDOĞDU, FATMA KUTLU; 273471; 108243; 109203
    Background: Kidney exchange has become a very common and important treatment alternative for patients suffering from serious kidney diseases with incompatible donors. Factors such as blood type, HLA matches and PRA existence are considered to determine compatibility. In a paired exchange, two incompatible patient-donor pairs switch their donors who are compatible with the other recipient. Currently, each hospital in Turkey operates individually in a decentralized manner using its own list. This list may contain patients having more than one incompatible donor, which differentiates the current work from those existing in literature. Methods: In this study, mathematical models are developed to propose an easy and practical approach for the paired kidney exchange problem in Turkey. Data are generated by employing a real data set provided by a hospital specialized in kidney transplantation. Results: The optimal solutions are obtained by using GAMS/CPLEX, and different scenario analyses are performed to measure the impact of "gender differences" and "age" on the solution. Furthermore, the original patient-donor list provided by the hospital is used to compare the model's solution with the planned transplantations. The study also evaluates a centralized approach which integrates all hospitals performing paired kidney exchange in Istanbul. Conclusions: As the optimal solution of the model is obtained in a basis of seconds, the developed approach offers an easy and applicable procedure for paired kidney exchange. Comparison of decentralized and centralized approaches reveals that the centralized approach is more favorable in terms of HLA compatibility and number of transplantations.
  • Publication
    Investigation of New Facility Location Fır Elvan Gıda
    (2019-06) Dinçer, Tutku; Tuncer, Müge; Özgür, Müge; İnce, Buse; Bayramoğlu, Feyzanur; Altınyar, Aydan; YÜKSEKTEPE, FADİME ÜNEY; 108243
    Elvan Gıda, established in 1952 as a small candy shop in Istanbul, started to manufacture sweet and chocolate to meet high quality confectionery demand with affordable prices. Elvan has 7 different production facilities located in Istanbul (5), Sakarya and Eskişehir. Currently, company is dealing with a problem of gathering all facilities in a single facility to eliminate fixed operating costs of each while covering desired increased capacity. In this study, an analytical approach will be proposed to solve the facility location problem of the company. First of all, the necessary data about distribution channels of finished goods, transportability, capacity of current and planned facilities, desired optimal distance to Ambarlı harbor and planned budget will be collected. According to determined criteria’s, AHP methodology will be used for selecting 5 promising potential alternatives by considering the executive boards’ evaluations. As a next step, a mathematical model will be developed to decide the least cost location alternative by considering both inbound and outbound transportation costs. Consequently, the optimal facility location with an aggregate layout plan will be proposed to ELVAN company.
  • PublicationOpen Access
    A comparative study of deep learning techniques in concrete crack detection: Convolutional neural networks and logistic regression
    (İstanbul Kültür Üniversitesi / Lisansüstü Eğitim Enstitüsü / Endüstri Mühendisliği Ana Bilim Dalı / Mühendislik Yönetimi Bilim Dalı, 2021) Rasul, Azhi Yassin; YÜKSEKTEPE, FADİME ÜNEY
    İnşaat alanlarında zorlu durumlarla günlük olarak karşılaşılmaktadır. Bu zorlukları yönetmek için yeni teknik ve yöntemler ortaya çıkmakta ve geliştirilmektedir. Klasik Makine Öğrenmesi (MÖ) ve Derin Öğrenme (DÖ) yöntemlerinin inşaat yönetimi alanında kullanılması da artmaya başlamıştır. Makine öğrenmesinin günlük problemleri çözme ve pratiğe dökülmesi için kullanılması, mühendislerin öne çıkarması ve başarması gereken bir görevdir. İnşaat alanlarında karşılaşılan problemlerden biri beton çatlağıdır. Çatlaklar yapılarda ortaya çıkan ve fark edilmesi zor olan hatalı oluşumlardır. Yapılardaki bozulmaları arttıracakları için erken zamanda tahmin edilmeleri çok önemlidir. Bu çalışma basit kameralarla toplanmış olan görüntüden oluşan bir veri seti için çatlak tahmininde DÖ yöntemlerinin kullanılmasını araştırmaktadır. Çatlak ve çatlak olmayan 40000 farklı görüntüden oluşan veri kümesi eğitim, doğrulama ve test olmak üzere üç gruba bölünmüştür. Bu veri kümesi, derin öğrenme yöntemlerinden biri olan ve yapay sinir ağları formundaki Evrişimsel Sinir Ağları (ESA) ve ikili sınıflandırma problem yöntemlerinden Lojistik Regresyon (LR) kullanılarak analiz edilmiştir. Son olarak, sonuçlar hem iki yöntem arasında hem literatürdeki mevcut çalışmalarla hem de gerçek hayat verileri ile kıyaslanmıştır. Aynı veri setinde hem ESA hem de LR modelleri iyi sonuçlar vermiştir ama ESA yöntemi doğruluk oranı ve kullanım açısından daha iyi olarak değerlendirilmiştir. Elde edilen sonuçlar umut vericidir ve ESA‟nın gerçek hayat inşaat yönetim uygulamalarında yakın gelecekte kullanılması beklenmektedir.
  • Publication
    Customer Response Prediction for a Specific Campaign in Penti via Data Classification
    (2019-09) Çiçekli, Sevra; Mutlu, Merve; Aral, Neslişah; YÜKSEKTEPE, FADİME ÜNEY; 297802
    Penti was established in 1950 in Turkey. It is growing in production and retail activities, expanding its offerings of mainly women's and girls’ socks, home wear and beachwear. Different campaigns are organized periodically in order to increase sales and customers are informed about the campaigns mostly by SMS regardless of their previous purchasing behavior. When informing the customers, there is no analytical tool used to find the right group of customers who will receive SMS about the campaigns. Therefore, the response rate to campaigns is not always as it is expected and cost of sending SMS is high. Number of SMSs that are bought from an outsource company and responses to the campaign directly affect the profit. With all these reasons, a study is made on creating an analytical tool just for a specific campaign in Penti. In this study, an analytical tool which will predict the possible responses of customers to a specific campaign is developed by using WEKA software. While developing this tool, different classification algorithms are used. Each method is compared in terms of their accuracy rates and the best method which has the highest performance is selected as the tool. At the end of the study, the analytical tool is shared with the company. By the help of this tool, SMSs can be sent to the customers considering important attributes and the company can reach the right group of people who will do shopping at stores after those informative SMSs.