Mühendislik Fakültesi / Faculty of Engineering
Permanent URI for this collectionhttps://hdl.handle.net/11727/1401
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Item Yöneylem araştırmasının yöntembilimi(1985) Kara, İmdatItem A goal programming approach for multi objective, multi-trips and time window routing problem in home health care service(2021) Dengiz, Asiye Ozge; Atalay, Kumru Didem; Altiparmak, FulyaThe structure of services in the health sector is changed by the epidemic diseases affecting the world, the population growth and developing technologies. Due to the advantages it provides, home health care (HHC) services are increasingly being demanded by patients. With the in-crease in demand for HHC, the interest of researchers in Home Health Care Routing Problem (HHCRP) is also increasing. In this study, HHCRP has been studied based on information gathered from a relevant unit of a State Hospital providing HHC services in Ankara. Due to the limited resources in the hospital under consideration, vehicles often need to be used for multiple rounds. Thus, the HHCRP is considered as a multi-tour routing problem. Besides, the problem has been created with time window constraints in order to ensure that the demands of the patients are met on time. Meantime, meeting all the patient demands and reducing the environmental impacts are two important goals in HHCRP. The reduction of the environmental impacts can be achieved by minimizing the carbon emission of the vehicles used in the HHC. Thus, the problem addressed in this study has been defined as a multi-objective, multi-trip and time-windows home healthcare routing problem (MTTW-HHCRP). Weighted goal programming (GP) method is used to solve the proposed problem. Test problems are randomly generated based on the data and the information obtained from the hospital in Ankara, and the solutions obtained through scenario analysis are evaluated to guide the decision-making process.Item Determination of periodic inspection time in pressurized equipment exposed to fatigue by estimating the probability of fracture(2021) Sozen, Levent; Yurdakul, Mustafa; Ic, Yusuf Tansel; 0000-0001-9274-7467; AGE-3003-2022It is essential to inspect the pressurized equipment such as vessels, pipes, heat exchangers, boilers, etc., which are under the influence of variable load periodically to minimize the possibility of damage occurring or early disclosure of existing damage. These inspections may be carried out at fixed time intervals or can be carried out at determined intervals depending on a risk assessment that considers settlement of the equipment, operating conditions, and the potential danger of the equipment's chemical contained. Within the scope of this study, we evaluate the thin-walled pressurized equipment under variable internal pressure load. Special attention is crucial to the hot points where the stress is relatively high for inspection of fatigue-related damage on the equipment. We know that stress concentration factors are critical in welded zones in thin-walled pressure vessels. Therefore, the fatigue crack formation in the welded joints is more likely than the equipment's base metal. As a result of the study, we present the probability of time-dependent damage under the effect of fatigue caused by variable internal pressure for butt welded joints. Also, we propose a new approach for periodic control planning. As a case study, damage probabilities of the fuel or gas pipelines operating under variable pressure are calculated based on the diversity of the mentioned parameters, and a new approach is provided to determine the most suitable periodic inspection interval.Item Development of a multi-criteria decision making model for the selection of appropriate robots for the aerospace industry(2021) Celek, Osman Emre; Yurdakul, Mustafa; İç, Yusuf TanselIndustrial robots have different capabilities and features according to their application areas and requirements. In a sector with highly specialized processes such as aerospace industry, accurate selection of an industrial robot to meet the requirements is a very complex and difficult process. The main challenge is that there are many appropriate robots for the aircraft manufacturing and assembly processes. In addition many technical criteria should be evaluated for determining the most appropriate robot among the industrial robots. In this study the MOORA and TOPSIS method, which are multi-criteria decision making methods are presented for the selection of appropriate industrial robots in the aerospace industry. A real case study related to the application of the methods is also included in the paper content.Item Analysis of the effect of the number of criteria and alternatives on the ranking results in applications of the multi criteria decision making approaches in machining center selection problems(2020) Ic, Yusuf Tansel; Yurdakul, MustafaMulti criteria machining center selection models are widely used in the literature. In the applications of multi-criteria decision making models, machining center selection criteria are directly taken from catalogues. It is known that to have a ranking model sensitive to the weights of the selection criteria, it is especially important to limit the number of selection criteria to 7 +/- 2. A similar proposal can be put forward for the number of machining centers. In this study, whether or not reducing the number of criteria and alternative machining centers make the ranking results more sensitive to the changes in the criteria weights is studied using Spearman's rank correlation test. The study results show that the ranking results become more sensitive with a reduced number of criteria and alternative machining centers.Item Heart sound recording and automatic S1-S2 waves detecting system design(2020) Aksahin, Mehmet Feyzi; Oltu, Burcu; Karaca, Busra KubraThe second leading cause of death in the world is cardiovascular diseases. Diagnosis of vast majority of cardiovascular diseases is made by listening to heart sounds by specialists (auscultation method). However, since the method of auscultation depends on the experience and hearing ability of the specialist, obtained results can be subjective. Therefore, digitization and visualization of heart sounds enables accurate, rapid and economical diagnosis of cardiovascular diseases, especially heart valve diseases. For this purpose, a device prototype that collects the heart sound from human body and also amplifies, filters, displays and records collected data on digital environment was designed in the first part of this study. In order to test the working accuracy of the designed device, clinical applications were carried out with the permission of the ethics committee and as the result of this application 15 heart sound recordings from 5 different disease groups(mitral insufficiency, mitral-aortic insufficiency, mitral-tricuspid insufficiency, mitral-aortic tricuspid insufficiency and healthy heart sound recordings) were collected.and obtained recordings were examined. The most effective parameter for the diagnosis of heart valve diseases is the location of the S1-S2 heart sounds. For this reason, in the second part of the study, a medical decision support system was established to detect the S1-S2 locations to assist physicians in their diagnosis. In this context, heart sounds are first filtered by discrete wavelet transform. Then, the S1-S2 waves in the filtered signal are made evident by the teager energy operator and rule-based algorithm. As a result, S1-S2 locations in normal and pathological data were detected with 98.67% sensitivity, 97.69% specificity and 98.18% accuracy.Item Improving the rapid office strain assessment method with an integrated multi-criteria decision making approach(2020) Delice, Elif Kilic; Can, Gulin Feryal; Kahya, EminNowadays, work-related musculoskeletal disorders (WMDs) are gradually increasing. This not only reduces work efficiency but also negatively affects workers' health. For this reason, it is important to design the working environment based on ergonomic principles in order to prevent WMDs before they occur. In addition, before starting ergonomic design improvement activities in the enterprises, it is necessary to identify the departments with high strain levels and evaluate the design of the office components in these departments. In this study, an integrated multi-criteria decision making (MCDM) approach was proposed based on the Rapid Office Strain Assessment (ROSA) method to determine the strain level caused by office components and to identify the departments to be ergonomically improved according to these levels. In the proposed approach, the strain level related to office components was evaluated by ROSA method. To determine the importance weights of office components on strain levels, Step-by-Step Weight Assessment Ratio Analysis (SWARA) was used. Weighted Aggregated Sum Product Assessment (WASPAS) method was applied to order the departments according to the strain levels. The proposed approach was implemented in a company operating in the aviation industry. As a result, the most important office component that increases the strain level was determined as the chair, while the Manufacturing Engineering and R & D departments were determined as the units with the highest strain levels. Additionally, by performing sensitivity and comparative analysis, changes in the departments' rankings were evaluated.Item An optimization for milling operation of Kevlar fiber-epoxy composite material using factorial design and goal programming methods(2019) Ic, Yusuf Tansel; Elaldi, Faruk; Kececi, Baris; Uzun, Gozde Onder; Limoncuoglu, Nur; Aksoy, Irem; 0000-0003-0592-6868; 0000-0002-2730-5993; AAI-1081-2020; AAG-5060-2019; F-1639-2011; AAC-4793-2019Kevlar fiber-epoxy composite material is extensively used in manufacturing areas because of the advantages of composite material's characteristics. It is usually processed by traditional machining methods but the drawbacks for determination of optimum cutting parameters might cause some material deformations during machining process. In this study, the cutting parameters are concurrently optimized by using the integrated 2k factorial design and goal programming methods for minimum delamination and minimum surface roughness of Kevlar fiber-epoxy composite and the best machining parameters have been obtained for the material. The results were compared with the results of the multi-criteria decision-based Taguchi methods.Item A novel approach for automatic detection and tracking of flying objects(2019) Pakfiliz, Ahmet GungorIn this study, a new method is presented to automatically detect and track flying objects through video systems that are used for surface to air tracking tasks. In this approach, a method has been developed in which Standard Deviation is used to determine the presence of a flying object. The measurement data is adapted to track, so that the flying object becomes more dominant than the background. In order to track the detected target in real time, Interacting Multiple Model Probabilistic Data Association with Amplitude Information (IMMPDA-AI) algorithm is used. Although the IMMPDA-AI algorithm is mainly a point tracking algorithm, in this study, its applicability to video tracking is shown. For this purpose, the amplitude information of the sampled video frames is encoded as point data and the tracking is performed on this data. Thus, an algorithm has been developed in which the target is automatically detected, track initiated and continued. The algorithm is evaluated for different maneuvers, target types and clutter situations, and successful results are obtained.Item Can Sleep Apnea be Detected by Heart Sounds?(2017) Yildiz, Metin; Tabak, Zeynep; Yetkin, SinanObjective: It has previously been shown that there are morphological changes in hearth sounds during respiration and holding breath. In this study, for the first time in the literature, it was investigated whether sleep apnea could be detected automatically from heart sounds by teaching various classifiers of time and frequency plane parameters which are thought to be able to characterize the morphological changes seen in heart sounds during apnea. Materials and Methods: For this purpose, heart sounds were recorded simultaneously with full polysomnography records from 17 people. Classification studies were performed by assigning feature vectors obtained from heart sounds to K nearest neighbors and support vector machines. Results: The best result with K nearest neighbor classifier was 48% accuracy, 100% selectivity level. With support vector machines classifier, 82% accuracy and 42% selectivity values were reached. Conclusion: According to these values, it is concluded that the parameters of the heart sound used in this study do not make it possible to diagnose the sleep apnea from the heart sounds.