Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/11727/4809
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Item An International Facility Design Project(2008) Lacksonen, Thomas; Dengiz, BernaThis paper describes an international facilities design project for Manufacturing and Industrial Engineering students. American and Turkish engineering students collaborated to create and implement the re-design of a Turkish wheelchair manufacturing facility. The company needed engineering assistance to improve the efficiency and increase the capacity of their existing factory. Turkish Industrial Engineering students went on-site to collect data and draw the existing facility layout. American Manufacturing Engineering students analyzed the data and developed new layout designs. Four American students traveled to Turkey between semesters to implement the initial phases of their design. In the second semester, the Turkish students simulated the new layout to see the performance improvements, completing their project. Student learning outcomes were positive for both groups of students. The paper explains critical steps in identifying projects and partners. Lessons are shown about successes and shortcomings in planning, operating, and communicating with design teams across cultures.Item Aintshop Production Line Optimization Using Response Surface Methodology(2007) Dengiz, Berna; Belgin, Onder; 0000-0001-6702-2608; K-1080-2019This paper deals with the problem of determining the optimum number of workstations to be used in parallel and workers at some stations using simulation optimization approach in a paint shop line of an automotive factory in Ankara, Turkey. In the optimization stage of the study Response Surface Methodology (RSM) is used to find the optimum levels of considered factors. Simulation model and optimization stage integration is used both to analyse the performance of the current paint shop line and determine the optimum working conditions, respectively, with reduced cost, time and effort.Item A Local Search Heuristic with Self-tuning Parameter for Permutation Flow-Shop Scheduling Problem(2009) Dengiz, Berna; Alabas-Uslu, Cigdem; Sabuncuoglu, IhsanIn this paper, a new local search metaheuristic is proposed for the permutation flow-shop scheduling problem. In general, metaheuristics are widely used to solve this problem due to its NP-completeness. Although these heuristics are quite effective to solve the problem, they suffer from the need to optimize parameters. The proposed heuristic, named STLS, has a single self-tuning parameter which is calculated and updated dynamically based on both the response surface information of the problem field and the performance measure of the method throughout the search process. Especially, application simplicity of the algorithm is attractive for the users. Results of the experimental study show that STLS generates high quality solutions and outperforms the basic tabu search, simulated annealing, and record-to-record travel algorithms which are well-known local search based metaheuristics.Item A Hybrid Simulated Annealing For A Multi-Objective Stochastic Assembly Line Balancing Problem(2008) Cakir, Burcin; Dengiz, Berna; Altiparmak, Fulya; Xia, GP; Deng, XQ; 0000-0003-1730-4214; AAF-7020-2021Asssembly line balancing is the problem of assigning tasks to the workstations, while optimizing one or more objectives without violating restrictions imposed on the line. In practice, task times may be random due to the worker fatigue, low skill levels, job dissatisfaction, poorly maintained equipment, defects in raw material, etc. When stochastic task times are taken consideration in assembly lines, balancing procedure is more complex due to the probability of incompleteness of stations times in a given cycle time. In this study, a multi-objective simulated annealing algorithm (m_SAA) is proposed for single-model, stochastic assembly line balancing problem with the aim of minimizing of smoothness index and total design cost. To obtain Pareto-optimal solutions, m_SAA implements tabu list and a multinomial probability mass function approach. The effectiveness of the proposed m_SAA is comparatively investigated using another SA using weight-sum approach on the test problems. Computational results show that m_SAA with multinomial probability mass function approach is more effective than SA with weight-sum approach in terms of quality of Pareto-optimal solutions.Item A hybrid ant colony optimization approach for the design of reliable networks(2007) Dengiz, B.; Altiparmak, F.; Belgin, O.; 0000-0003-1730-4214; 0000-0001-6702-2608; AAF-7020-2021; K-1080-2019This paper presents a new solution approach, which is a hybridization of ant colony optimization (ACO) and simulated annealing (SA), called (h_ACO) to design of communication networks. The design problem is to find the optimal network topology where total cost is minimum and all-terminal reliability is not less-than a given level of reliability. The effectiveness of the h_ACO is investigated comparing its results with those obtained by SA and ACO, which are basic forms of the h_ACO, and also GAs given in the literature for the design problem. Computational results show that the h_ACO is an effective heuristic approach to design of reliable networks.Item Estimating the COVID-19 Death Counts Using a Hesitant Fuzzy Linear Regression Depend on Race, Age and Location(2022) Dengiz, Asiye Ozge; Atalay, Kumru DidemThe COVID-19 pandemic that has struck the world has caused social and economic problems in people's lives. Many countries are trying to reduce the impact of the pandemic by taking precautions to prevent the spread of the virus and reduce the number of deaths. Despite the precautions, many people have contracted the virus and a significant number have lost their lives. This suggests that some factors about the exact mechanism of how people contract the virus and get sick are still unclear. Therefore, many researchers wonder if there are other factors that make people more susceptible to the COVID-19 virus. In this study, hesitant fuzzy linear regression (HFLR) models are applied depending on variables such as age, race, and place of residence that are thought to influence COVID-19 deaths. HFLR provides an alternative approach to statistical regression for modeling situations with incomplete information. The models include input and output variables as hesitant fuzzy elements (HFEs). The relationship between the considered variables and the number of deaths is examined using data related to people living in different states of the United States. In addition, HFLR is used as an estimation model due to the uncertainty in the data obtained from the Centers for Disease Control and Prevention (CDC). The proposed HFLR models are used both to estimate COVID-19 deaths and to determine the effects of selected variables on COVID-19 deaths. In this way, countries can estimate the risk of death for individuals given these factors and determine what precautions to take for high-risk groups.Item Risk Analysis and Process Improvement for Medical Devices with Integrated Method DEA and FMEA(2022) Yamandir, Merve Nil; Dinler, Esra; Atalay, Kumru DidemRisk analysis is the identification of factors, conditions, activities, systems, components that are important concerning risk. Evaluating the systems in terms of risk plays a critical role in the production of products that are especially important for human health. The washing process of the medical devices at the production stage is important in terms of ensuring the acceptable sterility assurance level of the product before sterilization. In this process, the risk factors that may affect human health emerge. Risk Priority Number (RPN) which is used in the Failure Mode and Effect Analysis (FMEA) is calculated for each factor and it is considered to be equally important in general. Sometimes it can be difficult to clearly show the importance of these effects. These invisible effects cause great costs for companies, and they can also affect human health at risk. In this study, risk analysis of the washing process in a company producing medical devices is performed. Risk prioritization is made by scaling risk types and their effects by Data Envelopment Analysis (DEA) method to eliminate the disadvantages in question. As a result of the study, the prioritization of risk types with different methods is compared.Item The Use of Petri Nets in Performance Analysis of Flexible Manufacturing Cell(2022) Bulca, Fatima Busra; Ic, Yusuf Tansel; Yurdakul, MustafaA Flexible Manufacturing Cell (FMC) is a system that consists of computer-integrated machines, automatic material handling systems, and robots. It produces different part types with minimal worker involvement. Many different methods, such as queuing systems and simulation models, have been applied in FMC modeling in the literature. This study aims to use Petri Nets (PN) in modelling complex FMCs. The study is carried out in the FMC located in the Advanced Manufacturing Systems Laboratory of Baskent University. The FMC consists of a CNC machining center, a material handling robot and a pallet, which has three work-piece carriage capacities. Processing times of FMC elements may vary due to reasons (the power usage performance, air supply efficiency, electrical power efficiency, etc.) arising from the mechanical structure of the system. This uncertainty needs to be taken into account when modeling the system. In this study, the uncertain (fuzzy) processing times associated with the transitions were caused by the mechanical structure of the system. In order to compare with the newly developed fuzzy models, the system was first modeled using Transition Time Petri Nets (TTPN), in which the running times associated with the transition times take precise values. On the other hand, for handling fuzzy values of the actual operating times in the FMC, two models namely, Partial-Fuzzy Transition Time Petri Nets (Partial-FTTPN) and Fuzzy Transition Time Petri Nets (FTTPN) are developed. The results of the three models are compared to analyze the benefits of combining "time uncertainties" resulting from the natural behavior of FMCs.Item A Genetic Algorithm for the Redundancy Allocation Problem with Repairable Components(2022) Sahin, Merve Uzuner; Dengiz, Orhan; Dengiz, BernaThe complexity of the structures of modern engineering systems in the communication and electronic fields, the demand for high reliable system evaluation methods has increased. While improving the system's reliability, the cost is also on the upswing. Redundancy allocation is important approach for designing telecommunication systems. The reliability is increased by increasing number of redundant components in a system. The Redundancy Allocation Problem (RAP) is the design of new systems with higher reliability using redundant components in parallel arrangement. This paper presents a genetic algorithm (GA) with discrete event simulation (DES) to solve RAP with repairable components. The promising proposed approach is illustrated and investigated by some RAP benchmark/test problems involving repairable systems.Item Opposition-Based Variable Neighborhood Descent Algorithm for the Traveling Salesperson Problem with Hotel Selection(2022) Akpinar, Ipek Damla; Kececi, BarisIn this study, The Traveling Salesperson Problem with Hotel Selection (TSPHS) is considered. TSPHS includes daily working time/distance restrictions. This constraint does not allow visiting all points at once. For this reason, the traveler stops (roosts) at a suitable waiting point (hotel) at the end of the day and continues the next day's trip from the point (hotel) where he stayed. There is no obligation to visit each hotel, and a hotel can be visited more than once. A set of ordered nodes starting and ending at a hotel is called a trip, and a set of ordered trips covering all nodes is called a tour. The primary objective of the problem is to minimize the number of trips. The secondary objective is to minimize the total distance of the tour, provided that the time/distance per trip does not exceed the daily working time limit. Since this problem belongs to the NP-hard problem class, the use of the heuristic method has an advantage in terms of the solution time. In our solution approach, the initial solution is obtained using The Nearest Neighbor Algorithm (NN). To improve this solution, the Opposition-Based Variable Neighborhood Descent (OBVND) is used. The performance of the algorithm is evaluated on the test problems in the literature using various criteria. The results are compared with the best solutions available in the literature. The overall results show us that the proposed OBVND approach can find better quality solutions in 2 out of 16 problems in the Set 1 data; in 24 out of 52 problems in the Set 2 data; and in 9 out of 38 problems in Set 3 data.