Browsing by Author "Aydogan, Emel Kizilkaya"

Now showing 1 - 6 of 6

An ant colony optimisation algorithm for balancing two-sided U-type assembly lines with sequence-dependent set-up times
(SPRINGER INDIA, 7TH FLOOR, VIJAYA BUILDING, 17, BARAKHAMBA ROAD, NEW DELHI, 110 001, INDIA, 2018) Delice, Yilmaz; Aydogan, Emel Kizilkaya; Soylemez, Ismet; Ozcan, Ugur; 0000-0002-4654-0526; 0000-0002-8253-9389; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü
Some practical arrangements in assembly lines necessitate set-up times between consecutive tasks. To create more realistic models of operations, set-up times must be considered. In this study, a sequence-dependent set-up times approach for two-sided u-type assembly line (TUAL) structures is proposed for the first time. Previous studies on TUAL have not included set-up times in their analyses. Furthermore, an algorithm based on the Ant Colony Optimization (ACO) algorithm, which is using a heuristic priority rule based procedure has been proposed in order to solve this new approach. In this paper, we look at the sequence-dependent set-up times between consecutive tasks and consecutive cycles, called the "forward set-up time'' and the "backward set-up time'', respectively. Additionally, we examine the "crossover set-up time'', which arises from a new sequence of tasks in a crossover station. In order to model more realistic assembly line configurations, it is necessary to include sequence-dependent set-up times when computing all of the operational times such as task starting times and finishing times as well as the total workstation time. In this study, the proposed approach aims to minimize the number of mated-stations as the primary objective and to minimize the number of total workstations as a secondary objective. In order to evaluate the efficiency of the proposed algorithm, a computational study is performed. As can be seen from the experimental results the proposed approach finds promising results for all literature-test problems.
Determining the priority waste in aluminum manufacturing sector using the smaa-2 method: A case study of kayseri
(Computers and Industrial Engineering, 2014) Aydogan, Emel Kizilkaya; Ates, Nuray; Uzal, Nigmet; Ozmen, Mihrimah; 0000-0002-0912-3459; AGÜ, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü; Uzal, Nigmet
Small and medium-sized enterprises (SMEs) constitute a major part of the Turkish economy, accounting for a large proportion of the country's businesses and total employment. Although the SMEs are known as important contributors to environmental pollution, the relative contribution of SMEs to the total environmental impacts of industrial is unknown. The most important environmental issues related with aluminum industries are emission of gases, wastewater and solid wastes from aluminum production. In multi-criteria decision making (MCDM) problems in some situations, decision makers (DMs) don't or can't express their preferences obviously. In these situations for decision making, stochastic multi-criteria acceptability analysis (SMAA-2) can be applied. In this study, a multi-criteria decision making model is presented to determine higher priority waste types (air and solid wastes, wastewaters) among the three firms. We used stochastic data by applying and the SMAA-2 results are given.
Developing a Decision-Support System for Waste Management in Aluminum Production
(SPRINGERVAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS, 2016) Ozmen, Mihrimah; Aydogan, Emel Kizilkaya; Ates, Nuray; Uzal, Nigmet; AGÜ, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü; Uzal, Nigmet
Industrial enterprises constitute a major portion of the world's economy, as well as a large proportion of a country's businesses and total employment. In Turkey, industrial enterprises are underdeveloped in terms of knowledge, skill, capital, and particularly accessing and benefiting from the advantages provided by modern information and communication technologies. Aluminum manufacturing has been reported to be the largest industry in Turkey with respect to production volumes and application fields. However, aluminum production is known to be an important contributor to environmental pollution, and the relative contribution of other related enterprises to the total industrial environmental impact is unknown. Environmental pollution sources can typically be classified into three categories: gaseous emissions, solid wastes, and wastewaters. The types of wastes produced by aluminum production vary based on the process line used, the variety of target products produced, and the production capacity of a given plant. As the capacities of facilities grow, the type and amount of waste become more variable. Therefore, the primary objective of this study is to determine the priority of each waste type in aluminum manufacturing industries. This study was conducted in the Industrial Zone of Kayseri in Turkey. Three different facilities that range in size from large to small based on their production volume, plant capacity, and variety of production are selected for this study. The priority of waste types was determined by combining the AHP and PROMETHEE II multicriteria decision methods. While wastewater was categorized as having the highest priority in large facilities, solid waste was determined to be the highest priority in medium and small facilities.
Green building envelope designs in different climate and seismic zones: Multi-objective ANN-based genetic algorithm
(ELSEVIER, 2022) Himmetoglu, Salih; Delice, Yilmaz; Aydogan, Emel Kizilkaya; Uzal, Burak; 0000-0002-3810-7263; AGÜ, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü; Uzal, Burak
In recent years, the major component of green building designs adopted by governments in order to reduce CO2 emissions as well as energy consumption is the green building envelope. The green envelope has the most important share in terms of thermal energy consumption, environment, and indoor comfort criteria. Determining the most suitable building envelope combination in the building life cycle is an important problem for designers. This study presents a new multi-objective approach that determines the most suitable green envelope designs for the buildings in different climate and earthquake zones, taking into account CO2 emissions, heating/cooling energy consumption, and material cost in terms of life cycle cost analysis. To this end, EnergyPlus building performance simulation program, artificial neural network (ANN), and genetic algorithm are used together. After the heating and cooling energy consumption, CO2 emissions, and material cost values are obtained for a certain number of the envelope alternatives with the EnergyPlus, ANN models that learn the working mechanism of EnergyPlus are trained according to these values. An ANN-based genetic algorithm procedure is developed to search the whole envelope alternative space by using the trained ANN models with EnergyPlus. The proposed approach allows searching in a very short time the whole alternative space, which is almost impossible to scan with EnergyPlus by reducing the time spent and the number of alternatives required for the design and simulation processes of the green building envelope. The proposed approach is performed for a design-stage city hospital structure in Turkey. Window type, the internal/external plaster, wall, and insulation materials along with the thicknesses of these materials, which consist of 46 different variables, are determined as envelope attributes for four different climate and seismic zones. The green building envelope designs obtained with the proposed approach are entered into EnergyPlus and the consistency of the results is compared. ANN models with an average accuracy of over 97% are developed. Without the CO2 emission cost in the life cycle cost, the mean absolute percent error (MAPE) values for each region are 0.67%, 0.6%, 0.58%, and 1.78%, respectively. With the CO2 emission cost in life cycle cost, the MAPE values for each region are 0.96%, 0.88%, 0.86%, and 0.43%, respectively. According to the obtained results, there is a consistency of over 99% between EnergyPlus and the proposed approach.
Multi-dimensional Sustainability Evaluation of Indigo Rope Dyeing with a life cycle approach and hesitant fuzzy analytic hierarchy process
(ELSEVIER SCI LTDTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, OXON, ENGLAND, 2021) Aydogan, Emel Kizilkaya; Fidan, Fatma Sener; Uzal, Nigmet; 0000-0002-2397-3628; AGÜ, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü; Aydogan, Emel Kizilkaya; Uzal, Nigmet
The dyeing process of denim fabric production has the highest potential for significant environmental and human health impacts of denim production, consuming vast amounts of water, chemicals, and dyes. This study aims to assess the sustainability of indigo rope dyeing (IRD) obtained by designing a new recipe with the chemical alternative assessment method. Not only environmental impacts, but also social, economic, and product quality dimensions were included in the multidimensional sustainability assessment. The hesitant fuzzy analytical hierarchy process (HF-AHP) method was used to determine the criteria weights of the determined dimensions. The environmental and social impacts of the existing and newly designed IRD process were evaluated using the gateto-gate life cycle assessment (LCA) and social life cycle assessment (S-LCA) approach. According to the LCA results, the green IRD process exhibited better performance in terms of all environmental impacts evaluated and the abiotic depletion potential of the conventional indigo IRD process can be reduced by 62.55% by applying the green IRD process. According to the HF-AHP results, the most important criteria were environmental impact with 33%, followed by social impacts with 27%, quality results with 23%, and economic results with 17% in assessing the IRD process's sustainability denim production. These results showed that the sustainability of the IRD process could be improved by substituting the chemicals and dyestuff with green alternatives.
Robust Multicriteria Sustainability Assessmentin Urban Transportation
(ASCE-AMER SOC CIVIL ENGINEERS, 2023) Gulcimen, Sedat; Aydogan, Emel Kizilkaya; Uzal, Nigmet; 0000-0002-8967-3484; 0000-0002-0912-3459; AGÜ, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü; Gulcimen, Sedat; Uzal, Nigmet
Developing methodologies to facilitate the planning of sustainable transport systems for decision makers (DMs) is becoming more critical. This study proposed a methodological framework for sustainable urban transportation to make decisions during urban transportation's design and planning stages. Urban transportation alternatives were evaluated by sustainability indicators that considered a triple bottom line approach's environmental, economic, and social aspects. To choose the best alternative sustainable transportation scenarios, two multicriteria decision-making (MCDM) methods, for example, a hesitant fuzzy analytical hierarchy process (HF-AHP) and multiple attribute utility model (MAUT), were integrated. First, eight sustainable transportation indicators that considered data availability from the transport sector were selected. The weights of the selected indicators were calculated using an HF-AHP. These indicators included carbon dioxide (CO2) emissions, energy consumption, depletion of nonrenewable resources, operational and maintenance costs, fuel and taxes, the number of fatalities or injuries, and motor vehicles for public transport per 10,000 population. Finally, sensitivity analysis was applied to validate the robustness. Based on HF-AHP results, the number of fatalities or injuries was the most significant among the eight indicators, with a 0.158 normalized weight (N-i). The results of this integrated methodology highlighted that Alternative 11, which was dominated by low-motorized vehicles (low-MVs), was the best sustainable alternative and Alternative 1 was the worst sustainable alternative, which was dominated by high-MVs with 0.69 and 0.27 total utility values, respectively. Low-motorized urban transportation alternatives showed higher sustainable performances than the motorized and high-motorized alternatives. This study proposed a novel and robust methodology for decisions on sustainable urban transportation projects and renovating current urban transportation systems.