Person: ORBAK, ALİ YURDUN
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ORBAK
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ALİ YURDUN
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Publication Effective factor analysis for chromium(vi) removal from aqueous solutions and its application to tuncbilek lignite using design of experiments(Hindawi Ltd, 2019-01-01) Orbak, Ilkun; Orbak, Ali Yurdun; ORBAK, ALİ YURDUN; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi; M-9216-2014Poisonous heavy metals in air, water, and soil produce global environmental problems that are considerable threats to humankind. To meet the local and international guidelines for heavy metal release, companies often use different approaches, such as chemical precipitation, chelating agents, or activated carbon produced by adsorption. One of these heavy and toxic metals is chromium(VI). Chromium(VI) is commonly used in many applications, such as dye fixation in the textile industry or as an anticorrosive agent in paints. The aim of this paper is to explore the factors affecting the removal of one of these deadly heavy metals, chromium(VI), from aqueous solutions. For this purpose, activated carbon from Turkish Tuncbilek lignite is prepared with both chemical and physical activation methods to investigate the adsorption behavior of chromium(VI). The effects of initial chromium(VI) concentration, adsorption temperature, and pH on adsorption are studied using a design of experiments method with a full 2(4) factorial design with center points. The Freundlich and Langmuir adsorption isotherms that are commonly used in chemical engineering are also applied both for predicting the amount of chromium(VI) adsorbed and confirming the validity and advantages of the obtained regression model. The results indicate that the design of experiments and regression can explain and support the design of new materials by using linear and physically meaningful equations instead of local nonlinear and empirical models that are usually insufficient. Additionally, three experiments were carried out in the liquid phase to test the activated carbon samples: chromium, chromium and sucrose, and chromium-sucrose-ion. A change in adsorption capacities of the activated carbon samples was observed. Sucrose was chosen for the experiments because it contains six carbon atoms in a slightly soluble structure. The results indicated that Tuncbilek lignite exhibits good adsorption capability.Publication Implementation of design for six sigma methodology on the car bumper production process(Inderscience Enterprises, 2021-01-01) Orbak, Ali Yurdun; ORBAK, ALİ YURDUN; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü.; 0000-0002-4921-4275; M-9216-2014Competition increases daily in any market; therefore, continuous improvement of product or service is an essential tool for survival and making an impact on the industry. Companies that have successfully implemented the six sigma method have gained the most from incorporating their design for six sigma (DFSS) programs into their production processes. The primary purpose of DFSS is to "design it right the first time" to avoid negative experiences in the production flow. In this study, the parameters involved in the design of a selected passenger-vehicle bumper are optimised in the process of commissioning a new product using the DFSS method. The DFSS method is discussed on the first two steps of implementation of the "define, measure, analyse, design, verify" (DMADV) protocol. By additionally implementing the house of quality (QFD) and failure mode and effects analysis (FMEA) approaches, a vehicle bumper that will meet the maximum level of customer requirements is produced.Publication Identification of factors affecting noise levels by using data mining and design of experiments analysis techniques: A novel experimental approach(Sage Publications, 2022-04-29) Orbak, Ali Yurdun; Aydın, Fikret Umut; Sharma, Shubham; Chohan, Jasgurpreet S.; Rajkumar, S.; ORBAK, ALİ YURDUN; Aydın, Fikret Umut; Bursa Uludağ Üniversitesi/Endüstri Mühendisliği Bölümü; Bursa Uludağ Üniversitesi/Fen Bilimleri Enstitüsü; M-9216-2014; ITL-4245-2023The sounds that are high enough, which negatively affect our understanding, are called noise. Although students are one of the main sources of noise at schools, noise adversely affects students' success. Schools' acoustics and the time when the noise measurement is made are usually considered to be other reasons for noise. In this study, noise measurements are collected in several of a metropolitan city's primary and secondary schools, and factors that affect noise significantly are investigated using 2(3) full factorial experimental designs. In addition, school teachers' perception of noise is analyzed by the Apriori algorithm. Results indicate that noise values exceed the limit values set by the WHO and noise regulations currently in effect in Turkey. Also, the schools with no acoustic insulation were noisier than those with minimum insulation. From the Apriori analysis, it is concluded that female teachers are more sensitive than male teachers about noise annoyance.Publication Mathematical model assisted six-sigma approach for reducing the logistics costs of a pipe manufacturing company: A novel experimental approach(Mdpi, 2023-02-01) Sharma, Shubham; Li, Changhe; Kumar, Raman; Singh, Sunpreet; Di Bona, Gianpaolo; ORBAK, ALİ YURDUN; Küçük, Metin; Akansel, Mehmet; AKANSEL, MEHMET; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi.; 0000-0002-4924-7587; M-9216-2014; ABE-6702-2020This research addresses and analyzes the results of a six-sigma approach used to optimize the logistics costs of a pipe manufacturing company. Two mathematical models are developed for containers to control the company's logistics. The Mathematical Programming Language (MPL) software is used to generate and solve these models. The results verify that the proposed mathematical models result in the company's logistics improvement, especially in the DMAIC (define, measure, analyze, improve, and control) cycle by providing flexibility in choosing the most appropriate containers for logistics.Publication Prediction of Turkish mutual funds' net asset value using the fund portfolio distribution(Springer, 2023-06-11) Yılmaz, Ümit; Orbak, Ali Yurdun; ORBAK, ALİ YURDUN; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü; M-9216-2014Accurate prediction of mutual funds' net asset value (NAV) has become increasingly important for investors. Mutual fund investors will be significantly supported by the development of models that accurately predict the future performances of mutual funds. Using these models will facilitate the selection of suitable mutual funds for investors who want to invest in the medium and long term. The aim of this study, using artificial neural networks and nonlinear autoregressive networks with exogenous inputs (NARX) methods and Levenberg-Marquardt (LM), Bayesian regularization (BR), and scaled conjugate gradient training algorithms, is to predict the NAV of two Turkish mutual funds, which are Deniz Asset Management First Variable Fund (DBP) and Istanbul Asset Management Short-Term Bonds and Bills Fund, with the funds' their portfolio distributions. For this purpose, prediction models were developed with these methods, training algorithms, and some specific hyperparameters and applied to the datasets of the funds examined in the study. The performances of the developed models were compared according to the method and training algorithm pairs for each fund. For performance evaluation, mean squared error, mean absolute percent error, and coefficient of correlation statistical measures are used. From the result, it can be clearly suggested that the NARX-BR pair outperforms other models for DBP, and the NARX-LM pair outperforms other models for IST.Publication Simulated annealing algorithm and implementation software for fabric cutting problem(Ege Üniversitesi, 2020-01-01) Eroğlu, Duygu Yılmaz; Orbak, Ali Yurdun; YILMAZ EROĞLU, DUYGU; ORBAK, ALİ YURDUN; Bursa Uludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü; 0000-0002-4921-4275; 0000-0002-7730-2707; AAH-1079-2021; M-9216-2014The development of loom technology has significantly increased the efficiency of fabric output in the textile industry. Additionally, preventing the occurrence of defects during the manufacturing process on the fabric is not easy. Therefore, after the production is completed, the aim is deciding the cutting location of the product, which has the defect map, to increase the first quality product quantity by considering the customer quality parameters. In this article, a decision support system has been developed to help the inspector in the final stage which will also prevent losses. The utilized algorithm is the Simulated Annealing algorithm, which is well known and rendered good results for different types of problems in the literature. In the study, a sample problem is used to explain the adaptation of the algorithm to the problem, and the design of the experiments is deployed to obtain the best parameter values for the algorithm. Finally, the software, which is prepared to use the algorithm in the real production environment, is introduced and the results of the performance analysis are evaluated. The results demonstrated that the developed software is capable of making high ratio first quality fabric decisions within seconds.