Bütünleşik imalat ortamlarında ürün ağacı yapısının imalat performansı üzerine etkisi

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Küresel rekabet nedeniyle, ürünlerin yaşam döngüsü kısalmış, müşteri istek ve beklentileri artmış, düşük maliyetli ve zengin ürün çeşitliliği arzu edilmeye başlanılmıştır. Bu nedenlerden dolayı geleneksel olarak fazla üretilip stoklanarak müşteri isteklerinin karşılanması fikrinden uzaklaşılmaktadır. Malzeme ihtiyaç planlaması kullanılmaya başlandığı 70’lerden günümüze kadar üretim işletmeleri için öncelikler değişmiştir. Önceleri üretmek önemliyken şimdilerde istenilen zamanda, istenilen fiyatta, istenilen kalitede ürün üretimi önem kazanmıştır. Bu nedenle müşteri beklenti ve isteklerini karşılayabilmek için işletmeler yeni arayışlara ve modern üretim planlama ve kontrol sistemlerine ihtiyaç duyulmuştur. Çok aşamalı ve çok çeşitli ürün üreten işletmelerin küresel rekabet ortamında rakipleri ile rekabet edebilmesi için gerçek zamanlı bir üretim planlama ve çizelgeleme sistemlerine ihtiyaç vardır. Bu nedenle işletmelerin sahip olacağı sağlıklı bir üretim planlama ve kontrol yapısı sayesinde, maliyetlerin düşmesine, müşteri siparişlerinin karşılanma oranının yükselmesine, gerçekçi bir teslim tarihi elde edilmesine, gelecek planlamalarının etkin bir şekilde yapılmasına imkan sağlayacak gerçek zamanlı sınırlı kapasite üretim planlama ve kontrol yapısı önerilmiş ve önerilen sistem üç farklı ürün ağacı yapısı, beş farklı öncelik kuralı ve teslim tarihinin belirlenmesi için kullanılan üç farklı k sabiti değeri kullanılarak geliştirilen benzetim ortamında test edilmiştir. Geliştirilen benzetim modelinde üç bağımsız değişken girdi olarak kullanılmış ve altı farklı performans ölçütünün sonuçlarına göre değerlendirilmiştir. Alınan sonuçlar, çok değişkenli varyans analizi ile test edilmiştir. Yapılan test ve değerlendirme sonucunda ürün ağacı yapısı bağımsız değişkeninin tek başına ve diğer bağımsız değişkenlerle beraber imalat performansı üzerinde etkili olduğu tespit edilmiştir. Geliştirilen yapının siparişe üretim yapan, çok seviyeli montaj ve imalat işlemlerinin beraber yürütüldüğü bütünleşik imalat ortamlarında başarı ile uygulanabileceği düşünülmektedir.Due to global competiveness, life cycle of products have been shortened, low costed and rich product varieties have been demanded. For this reason, the idea of production to make stock for customer demand has been eliminated. Material requirement planning has been using since 1970’s. Nowadays, priorities of companies have been changed dramatically. Previously production was an important subject, whereas production on-time, on-demand, good quality and low priced products have been ground. For this reason, to satisfy customer needs and demands, companies investigated new methods and production control systems. Companies which produced multi stage and multi variety products need real time production planning and scheduling system. For this reason, companies which have good production planning and control systems, proceed low cost, satisfaction of customer demand, realistic due dates, and finite capacity planning and control systems. In this thesis, 3 different product structures, 5 different priority rules, and 3 different k constants for determining due dates have been developed to use in simulation software systems. In the developed simulation model, 3 independent variables has been used as input and evaluated with results of 6 different performance criteria. Results obtained have been tested with multiple variable variance analysis. After testing and evaluating, independent variables of product structures has an effect on manufacturing performance as single and other dependent variables. Structure developed for this work has been considered as a successful environment. Experimental results have been obtained in make-to-order environment and multi stage assembly and manufacturing operations in integrated manufacturing environment

Kaba kümeleme teorisi ile veri tabanlarından bilgi keşfi

Bu tezin, veri tabanı üzerinden yayınlanma izni bulunmamaktadır.ÖZET Anahtar Kelimeler: Kaba Kümeleme, Bilgi Keşfi, Veri Madenciliği, Veri Tabanlarından Bilgi Keşfi. İşletmelerin sahip oldukları veri tabanlarında bulunana verilerin miktarı her geçen gün artmaktadır. Aynı zamanda küreselleşen dünyada işletmeler artık kendi bulundukları ülkelerde değil diğer ülkelerde de bulunan işetmelerle rekabet etmeye başlamışlardır. Rekabet ortamında işletmelerin ayakta kalabilmelerinin koşullarından biride güçlü bir finansal yapının yanı sıra ellerinde bulunan anlamlı bilgilerdir. Yeni bilgilerin elde edilmesi için; işletmelerin sahip oldukları tecrübe ve eski bilgilerine ek olarak veritabanlarında bulunan veriler içerisinde gizli kalmış bilgilerinde çıkarılması gerekmektedir. Araştırmacılar tarafından veritabanlarında bulunan verilerden nasıl bir yöntemle anlamlı ve yararlı bilgiler elde edilmesi gerektiği üzerinde çalışmalar yapılmış ve yapılmaktadır. Bu çalışmalar veri tabanlarından bilgi keşfi (VTBK) ve veri madenciliği (VM) adlandırılmaktadır. Bu tez kapsamında, genel bir giriş yapıldıktan sonra, ikinci bölümde veri tabanlarında bilgi keşfi ve veri madenciliğinin tanımları, amacı, modelleri, avantaj ve dezavantajları ve uygulama alanlarından bahsedilmiştir.Üçüncü bölümde; tıp, eczacılık, mühendislik, bankacılık, finans, pazar analizi, çevre yönetimi ve diğer gerçek hayat problemine başarıyla uygulanmış olan kaba kümeleme teorisinin temel felsefesi ve kavramları açıklanmıştır. Dördüncü bölümde ise kaba kümeleme teorisinin bir uygulaması gösterilmiştir. Son bölümde ise uygulamadan elde edilen sonuçlar ve öneriler sunulmuştur. vmKNOWLEDGE DISCOVERY IN DATABASES WITH ROUGH SET THEORY SUMMARY Key words: Rough Set, Knowledge Discovery, Data Mining, Knowledge Discovery in Databases The amount of data in databases of businesses increase day by day. At the meantime businesses are forced to compete not also with local companies although compete with global companies with the globalization. To survive in this competition, meaningful knowledge in the hand of companies have the same importance as financial structure. To obtain new knowledge; addition to experiences and old knowledge, extracting the hidden knowledge in datas on databases is required Currently, researchers about how to obtain meaningful and useful knowledge from databases are studying. These research are called knowledge discovery in databeses and data mining. In the scope of the thesis, after a general introduction, in second chapter definitions of KDD and DM, their purposes, models, advantages and disadvantages are mentioned. In third chapter, basic philosophy and concepts of rough set theory which successfully applied in many real-life problems in medicine, pharmacology, engineering, banking, finances, market analysis, environment management and others is explained. In fourth chapter, an applications of rough set theory is shown» In last chapter the consequences obtained from application and suggestions are presented. I

An integrated fuzzy-grey based approach to group decision making problem for a wagon company

Supplier Evaluation and Selection (SES) is one of the most crucial issues for many companies because of its strategic importance. Over the years a number of approaches have been presented to SES problems. SES problems are multi-criteria decision making problem involving both quantitative and qualitative criteria. Decision makers' (DMs) preferences on alternative supplier or on the criteria are often uncertain. So SES problems become more difficult. In order to overcome this difficulty, a Fuzzy-Grey based approach is suggested in this paper. We combined the favorable sides of Grey System Theory's (GST) power of mathematical analysis and Fuzzy Set's (FS) power of pointing out uncertainty for the sake of processing the uncertainty information. As the empirical study, a practical application proceeded for a leading wagon company in Turkey. A real numerical example is used to clarify the suggested approach and comparison results are presented with conclusion

An integrated fuzzy-grey based approach to group decision making problem for a wagon company

Supplier Evaluation and Selection (SES) is one of the most crucial issues for many companies because of its strategic importance. Over the years a number of approaches have been presented to SES problems. SES problems are multi-criteria decision making problem involving both quantitative and qualitative criteria. Decision makers' (DMs) preferences on alternative supplier or on the criteria are often uncertain. So SES problems become more difficult. In order to overcome this difficulty, a Fuzzy-Grey based approach is suggested in this paper. We combined the favorable sides of Grey System Theory's (GST) power of mathematical analysis and Fuzzy Set's (FS) power of pointing out uncertainty for the sake of processing the uncertainty information. As the empirical study, a practical application proceeded for a leading wagon company in Turkey. A real numerical example is used to clarify the suggested approach and comparison results are presented with conclusion

Price Prediction Using Web Scraping and Machine Learning Algorithms in the Used Car Market

The development of technology increases data traffic and data size day by day. Therefore, it has become very important to collect and interpret data. This study, it is aimed to analyze the car sales data collected using web scraping techniques by using machine learning algorithms and to create a price estimation model. The data needed for analysis was collected using Selenium and BeautifulSoup and prepared for analysis by applying various data preprocessing steps. Lasso regression and PCA analysis were used for feature selection and size reduction, and the GridSearchCV method was used for hyperparameter tuning. The results were evaluated with machine learning algorithms. Random Forest, K-Nearest Neighbor, Gradient Boost, AdaBoost, Support Vector and XGBoost regression algorithms were used in the analysis. The obtained analysis results were evaluated together with Mean Square Error (MSE), Root Mean Square Error (RMSE) and Coefficient of Determination (R-square). When the results for data set 1 were examined, the model that gave the best results was XGBoost Regression with 0.973 R2, 0.026 MSE and 0.161 RMSE values. When the results for data set 2 were examined, the model that gave the best results was K-Nearest Neighbor Regression with 0.978 R2, 0.021 MSE and 0.145 RMSE values

Automatic generation of variants depending on changes of product properties in a flexible manufacturing environment

Competition forces manufacturing systems to be flexible and to increase product variety and process complexity. These tasks depend on the flexible design of a bill of materials (BOM), one of the most important inputs in manufacturing planning and control systems. Product variety forces systems to generate BOMs with regard to product properties through a BOM pattern. A variant bill of materials provides a structure to manage product variability. In this study, an algorithm is designed to build a BOM pattern using computer-aided design and computer-aided manufacturing (CAD/CAM) data, and another algorithm is designed to generate variants with regard to product specifications. Genetic algorithm is used to generate new products to provide high product variability for testing algorithms. After the test, both algorithms are applied to a real industry problem. The BOM pattern is built automatically using CAD/CAM data, and variants are generated with regard to the pattern, and the results are discussed. (C) 2014 Elsevier Ltd. All rights reserved

A real-time inventory model to manage variance of demand for decreasing inventory holding cost

Recent production planning studies focus on real-time planning and dynamic scheduling to increase utilization and robustness. In these studies, real-time data is used for planning, but in most of them manufacturing systems and planning methodology are not transformed into a real-time system approach. The novel aspect of this study is the presentation of a model in which the manufacturing system has been designed as a real-time system that consists of real-time planning activities working with real-time data, and eliminating the safety stock. (C) 2016 Elsevier Ltd. All rights reserved

An expert system based material selection approach to manufacturing

Selection of proper materials for a diverse mechanism is one of the hardest tasks in the design and product improvements in various industrial applications. Materials play a vital and important function during the entire design and manufacturing process. The wrong selection of materials often leads to huge prices and ultimately results in product breakdown. Hence, the designers need to identify and select suitable materials with specific functionalities in order to attain the preferred output with the minimum cost concern and specific applicability. This paper tries to solve the materials selection problem by means of an expert system approach to manufacturing. According to this method either four or five different properties are inspected for each automotive part such as impact resistance, lightness, formability, corrosion resistance and low prices for bumpers; strength, formability, vibration absorption and low cost for flywheels; and strength, formability, corrosion resistance, biocompatibility and a small price for implants. Then, these were made more efficient using the expert system approach. Due to performing most of the above mentioned properties, polymeric materials {such as PP (polypropylene), HDPE (high density polyethylene) and PMMA (polymethyl methacrylate)} are selected for the bumpers; GFRPs (glass fiber reinforced plastics) and CFRPs (carbon fiber reinforced plastics) composites for high speed running, and cast iron and steel for low speeds for the flywheels; and finally stainless steel and polymeric materials {such as PVC (polyvinyl chloride) and PE (polyethylene)} were found to be the best materials for automotive parts. The selected materials were almost identical to those obtained by previous authors. (C) 2012 Elsevier Ltd. All rights reserved

Consumer Sentiment in Turkey, from Closure to the New Normal

The main aim of the study was to analyze consumer sentiment in the COVID-19 pandemic period in the context of Turkey. In this context, “expectations of consumers regarding the changes in their current income and general expenditures in the economic conditions brought along with normalization process” and “in what direction consumer sentiment would change in the 6-month period following the normalization process in Turkey” were investigated. Based on these research questions, a descriptive study was conducted by adopting a quantitative research method. The questionnaire method was employed in the collection of the study data. As the COVID-19 pandemic was still ongoing when the study was conducted, the data were collected through an online questionnaire by using the convenience sampling method. The data that were obtained from 1147 participants were analyzed by using descriptive statistics through SPSS 24 software. The results that were obtained demonstrated that almost half of the consumers anticipated a decrease in their income in the 6-month period following the normalization process, and that they expected their expenditures would be reduced. In addition, it was determined that consumers were pessimistic in terms of the potential changes that would occur in their personal savings and family living conditions. Hence, it was found that consumers did not expect a considerable improvement in their economic and living conditions in the 6-month period following the normalization process. As the results that were obtained from consumers’ expectations were conscious estimations, as discussed in the assumption of rational expectations theory, they support the estimations of this economic theory