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Öğe The Analysis of Low Use Reasons of Renewable Energy Sources in the Iron and Steel Industry with Fuzzy Analytic Hierarchy Process- Turkey Example(Institute of Electrical and Electronics Engineers Inc., 2021) Sanli, S.; Ersoz, F.Energy resources have gained importance due to the increasing need for energy every day. The lack of resources of developing countries, which use especially fossil fuels more, increases foreign dependency. Thus, it is important to use renewable resources, especially in the iron and steel industry, which is one of the sectors with intensive energy use. This study was designed to investigate the low use of renewable energy sources in the sector and implemented in Karabük, which is one of the pioneering cities in Turkey's iron and steel industry. In practice, AHP method, which is one of the Multiple Criteria Decision-Making methods, is combined with fuzzy logic and Fuzzy AHP (BAHP) method is applied. Four main criteria have been determined, namely "Technical", "Economical", "Social"and "Environmental"reasons that cause low use of renewable energy resources in the steel industry. With this study, which is a pioneer in revealing low use reasons of renewable energy sources in the iron and steel industry, effective factors were identified and the order of importance was found as economic, technical, environmental and social reasons. © 2021 IEEE.Öğe Comparison of Iron and Steel Production Defects Using Classification Algorithms(Institute of Electrical and Electronics Engineers Inc., 2021) Akinci, I.B.; Alobaidi, D.; Ersoz, F.The iron and steel industry are a strong foundation of economic development in the world. The iron and steel industry are directly related to the economic developments in the world market and the economic powers of the countries. It also provides input to all branches of industry. Data mining and techniques in this sector play an important role in the activities of corporate and large enterprises as a scientific method. It involves the processes of finding and modeling meaningful relationships between meaningless large chunks of data in an enterprise. Studies on the iron and steel industry in the world and in our country are very limited. Analyzing products in the iron and steel industry using data mining techniques will both save time and contribute to reducing the financial burden of operators. It is also thought that it can increase the preferability level by increasing the quality of the products offered to the customers. In this study, the data mining process of the iron and steel industry is defined and the data mining studies applied to some quality improvement problems in the production sector are examined, and the optimization of the process and quality parameters from the quality improvement problems are emphasized. In the application section, data mining techniques are used to determine the variables and levels that cause manufacturing defects in an industrial enterprise. To achieve this goal, the decision tree, which is one of the data mining classification methods, has been applied with the C5.0, CRT, CHAID and QUEST algorithms, the decision tree has been created with the highest accuracy C5.0 algorithm and the results have been examined. As a result of the analysis, the products produced by the industrial enterprise are classified according to production defects. © 2021 IEEE.Öğe Determination of Production Defects in Iron and Steel Sector by Data Mining(Institute of Electrical and Electronics Engineers Inc., 2019) Akinci, I.B.; Ersoz, F.The studies related to the production industry are limited in the world and in our country. Especially in iron and steel sector, quality levels of different types of products need to be monitored. The studies show that with the emphasis on the quality levels of iron and steel products, the product life span is prolonged, and price and sales superiority is provided in the products. Accordingly, the market value of the products increases and there is a minimum loss of product. The primary purpose of the enterprises that realize the importance of quality work and improvements is to support quality production by preventing or reducing defects in production. Therefore, scientific studies in this sector should be focused on. Data mining and techniques, which is one of the scientific methods in this sector, have been used effectively in institutional and large enterprises. Data mining makes a significant contribution to business managers and includes the processes of finding and modeling meaningful relationships among the meaningless large data stacks in the enterprise. At this point, it is possible to define data mining as a set of techniques and concepts that generate new information for decision-making processes. In this study, firstly the data mining process is defined, data mining studies applied to certain quality improvement problems in manufacturing sector are examined and the optimization of process and quality parameters from quality improvement problems is emphasized. In the application part, data mining techniques are used to determine the variables and levels that cause production defects in an industrial enterprise. To achieve this aim, K-Means algorithm, which is one of the multivariate statistical methods, was examined by clustering analysis and the results obtained were supported by discriminant analysis. As a result of the analyzes, the products produced by the industrial enterprise were classified according to the production defects. © 2019 IEEE.Öğe Effects of Financial Conditions on Photovoltaic System Design and Investment Process: An Application on Different Scenarios(Institute of Electrical and Electronics Engineers Inc., 2021) Ozcan, O.; Ersoz, F.In this study, the effect of change in financial conditions, which is very important for investment costs in the process of evaluating Turkey's solar energy potential, is examined by giving different case scenarios. Sizing of the photovoltaic system with 8.9 MW installed power are given which made for Izmir Organized Industrial Zone during the application phase. Production (simulated) and financial performance of the generated system have been compared to the cities of Izmir, Ankara, and Istanbul, which are located in different geographical regions of Turkey and are at a level of similar development from a socio-economic point of view. The investment return made for three city alternatives in the financial conditions of 2018, has been compared with the return provided in the conditions of 2019. Also, for three alternatives; the results of the different scenarios such as the investment costs to be incurred, the land costs in the investment regions, the energy procurement and other additional supports provided by the state are included in the study. In the photovoltaic investment performance; In addition to system sizing, regional selection, and state incentives, the impact of the financial conditions that are constantly changing has been seen to be very important. © 2021 IEEE.Öğe Estimating the cost of crude steel production: A machine learning approach(Institute of Electrical and Electronics Engineers Inc., 2021) Kapansahin, G.; Ersoz, F.Sacrifice stands for the production of goods and function, constitutes the costs of enterprises. Cost is also defined as the provision of consumed goods and functions by a production enterprise. Accuracy of enterprise activity analysis is very important in order to make appropriate decisions in enterprises. The consistency of the results ensures correct decision-making; provides right marketing and competitive advantage. Various elements are effective in the process of product costing. The items on the basis of product are examined one by one and the analysis is carried out to obtain the unit costs that reflect the reality. The aim of this study is to investigate the factors affecting the costs and to estimate the cost in the integrated system, with data mining classifying models in the process of billet production, in an a enterprise for the Iron and Steel sector. It is targeted to compare obtained estimation results with the costs presented inside the enterprise. © 2021 IEEE.Öğe Evaluation of the Applicability of Industry 4.0 Processes in Businesses and Supply Chain Applications(Institute of Electrical and Electronics Engineers Inc., 2019) Merdin, D.; Ersoz, F.Increasing the flexibility and effeciency of enterprises from procurement to sales provides a great competitive advantage for meeting consumer demands. Providing competitive advantage is possible through the effective implementation of innovative technologies of fourth industrial revolution in the all stages of supply chain process. In this context, research has been carried out for industry 4.0 applications at every stage of the supply chain process and the role of digitalization in the supply chain has been mentioned. In addition, views and in-depth data from 32 companies based in Turkey were collected by questionnaire and subsequently analysed in a detailed format with data mining methods. In this context, using the augmented reality glasses in supply chain operations, the robots used in production can adapt more quickly to the works, especially in the logistics sector. Also, the use of drone has an important place in the external logistics processes. It was also observed that the use of autonomous electric vehicles can reduce harmful environmental impacts, thereby providing optimum vehicle routing. In summary, increase in digital data and the end of the life of the robots used in the development of robot resulted in huge data dumps; the small size and volumes of the firms' warehouses made it difficult to properly use robots; managers had troubles adapting their digital visions to the changing times and processes; employees experienced difficulties during transitions from one system to another; and finally, it is unclear whether the country's current energy capacity is sufficient for the growth of smart factories. © 2019 IEEE.Öğe Process Improvement in Furniture Manufacturing: A Case Study(Institute of Electrical and Electronics Engineers Inc., 2018) Ersoz, F.; Ersoz, T.; Peker, H.Today, with the increasing competition, enterprises are working to increase the product quality in order to meet the demands of the customers and increase the market share. The Six Sigma philosophy that emerged in the 1970s is a study to reduce the costs of poor quality in the production and service process. In this study, Six Sigma philosophy was applied in order to reduce the cycle time of the diamond sofa product produced by a furniture enterprise. Firstly, the production line was examined in detail by SIPOC analysis method and the cycle times of the processes were collected by chronometry method. Then, statistical methods such as proj ect identification document, Pareto diagram, Fishbone diagram were used. The control of the change in cycle time in the production of diamond sofa was calculated by ARENA 9.0 simulation program. © 2018 IEEE.
