Sürdürülebilir Kalkınma Amaçları
Yayınlar
- MakaleYalnız künye2026Scopus SJRQ2Assessment of municipal water quality criteria in consideration of microbiological and physicochemical parameters using a fuzzy decision-making framework
Suiçmez, Özlem; Teke, Çağatay; Özdemir, Akın
Water is a significant element for the sustainability of life and is crucial for many aspects, such as agriculture, cities, ecosystems, industries, and people. This study focuses on municipal water quality assessments for urbanization activities and human health concerns when dealing with the sustainable city concept. For the first time, an integrated fuzzy decision-making framework is proposed to evaluate municipal water quality criteria with microbiological parameters, heavy metals, and other chemicals. For this aim, the eight main criteria and forty-four sub-criteria were specified to evaluate municipal water quality for a sustainable city. A case study was performed in Bayburt, Türkiye, to evaluate 130 water depots when dealing with a number of scenarios. Moreover, the Sustainable Development Goals (SDGs) 6.1 and 6.3 can be achieved through the study. Finally, this study presents how to develop safe and clean water management for the concept of a sustainable city.
- MakaleYalnız künye2025Scopus SJRQ1Optimization of surface modification parameters of fly ash with high calcium oxide (CaO) content to use as a filling material
Uçurum, Metin; Özdemir, Akın; Teke, Çağatay
Fly ash (FA) is the fine-grained waste product obtained by burning coal after being ground to specific sizes in thermal power plants, carried with flue gases, and kept in cyclones or electro-filters. Like every industrial waste, the possibilities of utilizing FA have been investigated, and it can be utilized as an additive in cement and concrete. Despite this, industrial waste, which increases daily in the world, brings many problems, especially environmental problems. For this reason, alternative usage areas of the waste in question are constantly being investigated. In this paper, FA containing approximately 50 % CaO from Afşin-Elbistan, Turkiye was processed with stearic acid in a planetary mill to be used as a filling material in industrial products, and it has a grain size of 68.10 μm on a d50 basis, a specific surface area (SSA) of 176.40 m2/g and a contact angle of 13.89. An optimization and characterization study was conducted to make the hydrophilic surface structure hydrophobic by mechanochemical surface modification. Also, surface modification parameters, such as operational speed (rpm), ball filling ratio (%), FA filling ratio (%), pulp density, stearic acid dosage (% of FA), and modification time (min.) were optimized with the D-optimal experimental design. Based on the optimum surface modification parameters, a coated fly ash (CFA) product was obtained with an active ratio of 99.70 %, a contact angle of 95.06o, a medium size (d50) size of 10.60 μm, and an SSA of 926.90 m2/g.
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İncele - MakaleAçık Erişim2024Green Supplier Assessment with Fuzzy Expert System Approach
Teke, Çağatay
Today, reasons such as increasing pollution on a global extent and limited raw material resources are increasing the interest in green supply chain management (GSCM). GSCM includes the processes starting from the very beginning of the production process of a product, completing the production, delivering the product to the customer, and recycling the product at the end of its useful life. Its main purpose is to eliminate or minimize the damages caused to the environment in all of these processes. In order to achieve this goal, it has great importance to assess the suppliers, which are one of the most important components of the production process, in terms of becoming a green supplier. In this study, a fuzzy expert system model has been developed to assess the green suppliers based on green production technology, environmental management system, pollution control, product cost, quality, and lead time criteria. Mean Square Error (MSE) and coefficient of determination (R2) have been calculated to measure the performance of the developed model. These calculated values show that the green supplier assessment performance of the developed model is quite high.
AtıfOpenAlex1TR Dizin1
İncele - MakaleAçık Erişim2024Scopus SJRQ4PREDICTION OF TURKEY'S COTTON SOCK EXPORTS TO GERMANY USING DEEP LEARNING APPROACH; [TÜRKİYE'NİN ALMANYA'YA PAMUKLU ÇORAP İHRACATININ DERİN ÖĞRENME YAKLAŞIMI İLE TAHMİNİ]
Özbek, Ahmet; Teke, Çağatay
Cotton socks are a strategic export product for Turkey. Therefore, the aim of this study is to forecast Turkey's exports to Germany, the world's largest cotton socks market. In order to achieve this objective, the determinants of exports were identified by analysing the literature. Then, expert opinion was sought to determine the importance of these factors for Turkey's cotton socks exports to Germany. Using the deep learning model created from the factors determined as a result of the expert opinion, the prediction of the export of Turkish socks to Germany was realised. A success rate of 96% was achieved with the prediction.
AtıfScopus1OpenAlex1TR Dizin1İncele - MakaleAçık Erişim2023Implementation of Fuzzy Linear Programming Approach for More Accurate Demand Forecasting in a Make-to-Stock Company
Teke, Çağatay
Demand forecasting is of crucial importance for make-to-stock companies because product demand is uncertain and it changes with time. Fuzzy linear programming (FLP) can be an optimum approach for such uncertain situations. In this study, the FLP model was used for more accurate demand forecasting in a make-to-stock company. Demand forecasting study was carried out according to the FLP method and linear programming (LP) method. Solutions of FLP and LP were compared in terms of imputed shortage cost, inventory carrying cost, and net profit. Results show that the applied FLP method is more advantageous than LP as it provides a 67% decrease in costs and a 15% increase in net profit.
- MakaleAçık Erişim2022Bireylerin Koroner Arter Hastalığı Risk Seviyesinin Bulanık Uzman Sistem Yaklaşımı İle Belirlenmesi
Teke, Çağatay
Koroner Arter Hastalığı (KAH) dünya genelinde insanların hayatını kaybetmesine sebep olan en önemli hastalıklardan biridir. Tıp alanında yaşanan gelişmeler bu hastalığın tedavisini kolaylaştırsa da risk faktörlerinin belirlenmesi ve değerlendirilmesinde hala birtakım yetersizlikler söz konusudur. Bu çalışmada, KAH ile ilgili yaygın belirti ve şikayetleri olan bireyler göz önüne alınarak tanıda kullanılan çeşitli risk faktörleri belirlenmiştir. Ayrıca bulanık uzman sistem yöntemi kullanılarak bireylerin KAH risk düzeylerini tespit etmek amacıyla bir yapay zeka sistemi geliştirilmiştir. Tasarlanan sistem kural tabanlı olup, bu kural tabanı yapısı tıp uzmanlarından edinilen bilgilerle oluşturulmuştur. Sistem, bireylerin hastalık riskini azaltmak için kendi kendine risk değerlendirmesi ve özelleştirilmiş öneriler sunmaktadır. Bu sayede koroner arter hastalığından muzdarip kişilerin sayısındaki artış önlenebilir veya geciktirilebilir.
AtıfOpenAlex1TR Dizin1İncele - MakaleAçık Erişim2022Scopus SJRQ2Determination of flow distance of the fluid metal due to fluidity in ductile iron casting by artificial neural networks approach
Teke, Çağatay
Ductile irons (DIs) have properties such as high strength, ductility, and toughness, as well as a low degree of melting, good fluidity, and good machining. Having these characteristics make them the most preferred among cast irons. The combination of excellent properties, especially in DI castings with a thin section, make it an alternative for steel casting and forging. But in the manufacture of thin-section parts, fluidity characteristics need to be improved and the liquid metal must fill the mold completely. The fluidity of liquid metal is influenced by many factors depending on the casting processes such as material and mold properties, casting temperature, inoculation, globalization, and grain refinement. In this study, an artificial neural network (ANN) model has been developed that allows for determining the flow distance of the liquid metal in the sand mold casting method under changing casting conditions of DI. Thus, the flow distance was estimated depending on the cross-sectional thickness during the sand casting under changing casting conditions. The experimental parameters were determined as casting temperature, liquid metal metallurgy quality, cross-sectional thickness, and filling time. Filling modeling was performed with FlowCast software. When the results were examined, it was seen that the developed ANN model has high success in predicting the flow distances of the liquid metal under different casting conditions. The calculated coefficient of determination (R2) value of 0.986 confirms the high prediction performance of the model.
AtıfScopus4WoS4İncele - MakaleAçık Erişim2021Scopus SJRQ3A novel approach to finding optimum operating conditions of design factors for the grinding experiment
Uçurum, Metin; Özdemir, Akın; Teke, Çağatay; Tekin, İlker
The efficiency of grinding experiments is an important issue for many industries. In this paper, a central composite design-based methodology was proposed to investigate the four design factors that affect the particle sizes. The four design factors were specified as mill speed (% of Nc), ball filling ratio (fc), powder filling ratio (jb) and grinding time (min). Another important issue was how to obtain an optimum operating condition for four design factors. For this particular purpose, a novel dual response optimization model was proposed using the particle sizes (d 10, d 50, and d 90) and the span value concept. This proposed approach was compared to the desirability function-based optimization concept. The verification study of the experiment was also carried out. The results of the grinding experiment runs showed that the optimum operating conditions were mill speed 73.495% of Nc, ball filling ratio 0.354, powder filling ratio 0.157, and grinding time 70 min. In addition, d 10, d 50, and d 90 were found 3.31 µm, 12µm, and 45.6 µm, respectively. The span value was also found at 3.52.
AtıfScopus3WoS3OpenAlex4İncele - MakaleAçık Erişim2021Scopus SJRQ3A novel weighted mean-squared error optimization model to obtain optimal conditions of adsorption factors for a lead removal process
Özdemir, Akın; Teke, Çağatay; Serencam, Hüseyin; Uçurum, Metin; Gündoğdu, Ali
Lead (Pb) removal process from wastewater is an important issue to prevent health problems for people. For this particular purpose, a low-cost adsorbent may be beneficial for improving the adsorption capacity for the Pb removal process. The aims of this paper are four-fold. First of all, a D-optimal experimental design was selected to reduce experimental runs and its cost. Second, the effect of four adsorption design factors, stirring speed (rpm), adsorbent dosage (g), pH level, and initial metal concentration (ppm), was examined. Also, the yellow natural stone, which is from Bayburt, Turkey, was used as a cheap adsorbent for the Pb removal process from the solu-tion. Third, a novel weighted mean-squared error optimization model was developed to obtain optimal adsorption levels for adsorption factors. Besides, a verification study was conducted to verify the results of the adsorption experiment. Finally, the lead (Pb(II)) removal capacity of the yellow Bayburt stone was obtained to be 46.031 mg/g, and the results of the experiment from the proposed methodology showed a good performance for the removal study.
- MakaleAçık Erişim2019Scopus SJRQ2Modeling design parameters with taguchi experimental method for obtaining operating conditions for cu(Ii) removal through adsorption process
Serencam, Hüseyin; Özdemir, Akın; Teke, Çağatay; Uçurum, Metin
One of the environmental concerns deals with the removal process of pollutants in water and wastewater. In this paper, a removal process was used to eliminate pollutants in water and wastewater. The aim of this paper was to obtain an optimum adsorption condition for the highest metal ions adsorbed (MIA) mg/g. For this particular purpose, a Taguchi L18 design was conducted. In addition, the signal-to-noise ratio was analyzed for optimum adsorption levels. The analysis of variance was also performed to evaluate the effect of each adsorption condition on MIA (mg/g) values. Moreover, an optimization model was also proposed to find the best optimal setting of adsorption levels. Then, the confirmation tests were performed using optimum coded levels of the adsorption parameters for the verification purpose. The results of the experimental study showed a good performance that Cu(II) removal capacity was found to be 43.66 mg/g. To the best of our knowledge, this research is the first to study natural stone as an efficient, inexpensive and cheap adsorbent for the removal process.
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