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Öğe An Investigation of the Adaptation of Turkish Textile Enterprises to Industry 4.0(İstanbul Üniversitesi, 2021) Özbek, Ahmet; Yıldız, Aytaç; Alan, Mehmet AsifIndustry 4.0 is a new understanding of production and is based (to a great extent) on the removal of people from production by radically changing the understanding of people-oriented production – a concept that has dominated for a long time. This understanding is becoming more widespread day by day and it is predicted that the future will mean a better understanding of production. Therefore, it is anticipated that adaptation to this understanding will be one of the determining factors in the future success of enterprises. In this study, it was aimed to investigate the adaptation of textile companies operating in Turkey to Industry 4.0. Within the scope of the study, a questionnaire was prepared to analyze the perspectives of textile companies towards industry 4.0 and their expectations from the industry 4.0 technologies they use. The questionnaire was applied to 67 textile companies that ranked in the top 500 large enterprises of the Istanbul Chamber of Industry (ISO) in 2017 and 2018 and the data obtained were analyzed. According to the results of the analysis it was determined that the technology that businesses use the most is ERP. Due to the high investment cost, it has been determined that only half of enterprises invest in industry 4.0 technologies, that they believe that industry 4.0 is applicable in the textile industry, that to invest in these technologies will increase productivity and reduce costs, and as a result, the highest increase in efficiency will be achieved.Öğe APPLICATION OF DEVELOPING CLOTHING RECOMMENDATION SYSTEM WITH ARTIFICIAL INTELLIGENCE TECHNIQUES(Chamber of Textile Engineers, 2024) Özbek, Ahmet; Altuntaş, Volkan; Erdoğan, NaileThis study aims to develop a clothing recommendation application for users who possess a large number of clothes but have limited time due to their intense work tempo. This application aims to assist them in using their clothes effectively, reducing the time spent on selecting outfits, and dressing fashionably. In the process of developing this application, firstly, the criteria influencing the user’s clothing preferences were determined. Subsequently, a wardrobe dataset was created based on the established criteria. Following this, methods for suggesting clothes were explored. As a result of the research, it was decided to utilize association rule analysis, multidimensional clothing representation coding, and weighted L1 distance methods for clothing recommendation in this study. In the application phase, experiments were conducted using the dataset associated with the chosen methods. It has been determined that the application developed in this study gives successful results in suggesting clothes suitable for user preferences. © (2024), (Chamber of Textile Engineers). All rights reserved.Öğe APPLICATION OF DEVELOPING CLOTHING RECOMMENDATION SYSTEM WITH ARTIFICIAL INTELLIGENCE TECHNIQUES(2024) Özbek, Ahmet; Altuntas, Volkan; Erdogan, NaıleThis study aims to develop a clothing recommendation application for users who possess a large number of clothes but have limited time due to their intense work tempo. This application aims to assist them in using their clothes effectively, reducing the time spent on selecting outfits, and dressing fashionably. In the process of developing this application, firstly, the criteria influencing the user's clothing preferences were determined. Subsequently, a wardrobe dataset was created based on the established criteria. Following this, methods for suggesting clothes were explored. As a result of the research, it was decided to utilize association rule analysis, multidimensional clothing representation coding, and weighted L1 distance methods for clothing recommendation in this study. In the application phase, experiments were conducted using the dataset associated with the chosen methods. It has been determined that the application developed in this study gives successful results in suggesting clothes suitable for user preferences.Öğe SELECTION OF SOCKS EXPORT MARKETS FOR TURKEY USING MULTICRITERIA DECISION MAKING METHODS(Yildiz Technical University, 2020) Yildiz, Aytaç; Özbek, AhmetExport provides foreign exchange inflow and reduces unemployment and is, therefore, an important field of economic activity promoted by every country. Turkey is the sixth-largest exporter in the socks industry, which is a strategic export product. In this context, it wants to take first place by increasing its export volume. For this, it must choose the markets which will export well. However, there are many criteria that are effective in selecting the export market place and are independent of exporting countries. It is beneficial to use multicriteria decision-making (MCDM) methods in the solution of such problems. The aim of this study is to select the most suitable export market to increase Turkey’s socks export volume. Firstly, a survey of export market selection criteria is developed based on a literature review. The survey is completed by export specialists of socks exporting companies in Turkey to determine the most important criteria in the selection of socks export markets. Afterward, between 2014-2018 criterion data of the top 11 countries accounting for 70 percent of the world's total socks imports are derived from the Trade Map Database. 2020 values were obtained using regression analysis. TOPSIS (Technique for Order-Preference by Similarity to Ideal Solution), GRA (Grey Relational Analysis) and ANP (Analytical Network Process) methods are used to evaluate the alternative socks export markets. Sensitivity analysis is performed using TOPSIS, GRA and ANP data. The results are compared to select the best export market for the Turkish socks industry. © 2020 Yildiz Technical University.
