YÖK Akademik
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Publication Development of a Restraint System for Rear-Facing Car Seats(Machines, 2023-01-01) Himmetoğlu, Selçuk; Yavuz, SametIn self-driving vehicles, passengers can set their seats in an unconventional seating position, such as rear-facing. Sitting in such an orientation can increase the risk of whiplash in the head-and-neck system in a frontal impact, as frontal crashes usually have higher severities compared with rear-end crashes. This paper shows that a forward-facing front seat optimised for rear-impact protection needs to be redesigned to be used as a rear-facing seat. In the second and main part of this paper, a restraint system for rear-facing car seats is developed, and frontal impact simulations with 64 km/h of delta-V are used to evaluate its performance. The designed seating system comprises two rigid torso plates, a fixed recliner and an energy absorber under the seat pan. Without using the developed restraint system, the 50th percentile male human model is exposed to neck shear forces exceeding 600 N. With the developed restraint system, neck shear forces are less than 350 N in frontal impacts with 64 km/h of delta-V. Apart from whiplash, the risk of head, chest, lower extremity and lower back injuries are also evaluated. The results confirm that the developed restraint system successfully protects the occupant since all assessment criteria values are lower than the injury assessment reference values.Publication Çok Amaçlı Tedarik Zinciri Optimizasyon Modelleri için Kapsamlı bir Literatür Araştırması(2023-01-01) güven; Güner, Gürkan GüvenPublication Sürdürülebilir Sağlık Yönetimi Optimizasyonu Kapsamlı Bir Literatür Araştırması(2023-01-01) Güner, Gürkan GüvenPublication Düzensiz Operasyon Yönetimi için Entegre Havayolu Çizelgeleme Yaklaşımı Karışık Tam Sayılı Doğrusal Olmayan Programlama ve Tavlama Benzetimi(2024-01-01) S. Erol; Güner, Gürkan GüvenPublication Publication A Literature Review on Master Production Scheduling Problems in the Automotive Industry(2023-01-01) Güner, Gürkan GüvenIn recent years, production by customer has been adapted to a very large number of industries. One of them is the automotive industry. The aim is to ensure low unit cost mass production processes and fulfill each production requirement. Production according to customer request requires flexible manufacturing equipment. In addition, this production requires a versatile (multi-tasking) and highly equipped workforce. In the automotive industry, the arrangement of end products according to customer specification requires considering a large number of optional (non-mandatory) parts. This results in a great variety of processing times at different stations of the assembly line. Multivariate and mixed-model production assembly lines in the automotive industry require five key planning problems to be considered. These; line balancing, master production scheduling, production sequencing, material flow control, and reordering. The master production scheduling problem for multivariate and mixed-model assembly lines is aimed at assigning each variant of a basic product type to production periods, depending on customer preferences. This problem requires anticipating the negative effects of an unbalanced model sequence at a low planning level (in the early stages of the planning process) and acting accordingly. This study deals with the master production scheduling problems applied in the automotive industry and provides a comprehensive literature search on the topic touched on by a limited number of studies. In addition, the dependency between master production scheduling and production sequencing and heuristic solution approaches were analyzed in detail in the study. The presented literature search is intended to serve as a guide for decision makers for the master production scheduling problems considered in the automotive industry.Publication A Comprehensive Literature Survey on Logistics Strategy and Supply Chain Optimization in the Biomass Energy Sector(2023-01-01) Güner, Gürkan GüvenPublication Literature Review on Sustainable Renewable Energy Supply Chain Optimization A Focus on Heuristic and Metaheuristic Methods(2023-01-01) Güner, Gürkan GüvenThe transition towards sustainable energy systems has necessitated the optimization of renewable energy supply chains. This literature review aims to explore the state-of-the-art approaches, with a specific focus on heuristic and metaheuristic methods, employed for optimizing sustainable renewable energy supply chains. Metaheuristics, which are higher-level strategies for guiding search processes, have demonstrated great potential in tackling complex optimization problems with diverse constraints and objectives. Genetic algorithms, simulated annealing, ant colony optimization and particle swarm optimization are some of the examples for the metaheuristic methods. The review emphasizes their ability to provide near-optimal solutions, handle uncertainties, and optimize multiple conflicting objectives. This literature review synthesizes and analyzes the existing research on heuristic and metaheuristic methods for optimizing sustainable renewable energy supply chains.Publication Stochastic Optimization in Renewable Energy Systems A Comprehensive Literature Review(2023-01-01) Güner, Gürkan GüvenPublication A New Solution Approach for Optimizing the Integrated Airline Scheduling Problem in The Management of Irregular Operations(2023-01-01) Güner, Gürkan Güven; S. ErolObjective ⎯ The aim of this study is; for airline companies that have incurred unprecedented costs in the aviation sector due to the global pandemic that has emerged unexpectedly today; in order to solve the problem of flight, aircraft and crew scheduling that they have to reschedule within a very short time frame within the scope of the management of irregular events; to propose a method that can produce solutions with an integrated optimization approach, and to be able to advise decision makers in the airline sector on cost management and to contribute to the literature on airline management. Design / Methodology / Approach ⎯ Within the scope of the study, all the existing optimization solution approaches proposed for airline scheduling problems in the literature were tried to be examined and analyzed. The ways in which the studies handled airline scheduling problems discretely or integratedly, the mathematical optimization models they proposed and the heuristic/meta-heuristic methods used were reported. In the light of the data obtained after a comprehensive literature research, a new mathematical model using mixed integer nonlinear programming is proposed for the integrated airline scheduling problem. Whether the proposed mathematical model could solve a small-sized airline scheduling problem was tested through GAMS software. In order to achieve the best result, the considered integrated problem was solved with Simulated Annealing meta-heuristic solution approach using R software. Results ⎯ With the proposed new mixed integer nonlinear mathematical model, it has been proved that a small-scale integrated airline scheduling problem of Anadolu Jet airline company can be solved. It has also been reported that the proposed Simulated Annealing meta-heuristic solution approach to achieve the best result can also solve the problem in a short time with R software. Originality / Value ⎯ This study makes a new contribution to the literature on the solution of the integrated problem, proving that the problem of integrated flight, aircraft and crew rescheduling can be solved by proposing a new mixed integer nonlinear programming model that has not been previously considered in the literature.