Endüstri Mühendisliği Bölümü / Department of Industrial Engineering

Permanent URI for this collectionhttps://gcris3.etu.edu.tr/handle/20.500.11851/277

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Farklı Plaftormlarda Kullanılan Benzer Helikopter Motorlarının Güvenilirlik Analizi Yaklaşımı
(Academy Global Publishing House, 2024) Tanın, Halit Kutay; Görgülüarslan, Recep Muhammet; Tekin, Salih
Günümüz havacılık dünyasında birçok üretici firma, çeşitli görev profillerine sahip farklı sınıflardaki hava araçlarına benzer hava aracı motoru entegre etmekte ve kullanıcılarına sunmaktadır. Yeni bir hava aracı motoru geliştirmenin maliyetinin yüksek olması, takvimsel sınırlamalar ve sertifikasyon süreçlerinin zorluğu, üretici firma tarafından başka platformlarda uzun süreler kullanılmış ve tecrübe edilmiş motorların yeni geliştiren platformlara entegre etmesini önemli hale getirmektedir. Bu çalışma, hafif sınıf taarruz helikopterinde kullanılan turboşaft motorunun orta sınıf genel maksat helikopterinde kullanıldığı durumdaki güvenilirlik analizlerini kapsamaktadır. Hafif sınıf taarruz helikopterinde kullanılan motorun; güvenilirlik analizi hesaplamaları uzun yıllar süren sertifikasyon testleri, motor dayanım testleri, performans analizleri ve platform / motor entegrasyon testlerinden elde edilen saha verileri analiz edilerek gerçekleştirilmektedir. Aynı motorun orta sınıf genel maksat helikopterinde kullanıldığı durumda, güvenilirlik değerlerinin farklı uçuş ve görev profillerine göre yeniden hesaplanması ihtiyacı doğmaktadır. Turboşaft motorun kompresör, gaz jeneratör türbini, güç türbini, yanma odası, şaft, disk gibi temel komponentleri gerilme/kopma, korozyon ve Düşük Çevrimli Yorulma (Low Cycle Fatigue) hata modlarına sahiptir. Platform görev profiline göre hesaplanan Toplam Motor Döngüsü (Total Accumulated Cycle) parametresi her iki platform için elde edilerek düşük çevrimli yorulma ölçekleme faktörü hesaplanmıştır. Farklı görev profillerine göre dağılımı çıkartılan gaz jeneratör türbin giriş sıcaklık değerinden ise(T4,5) gerilim / kopma, korozyon ölçekleme faktörü hesaplanmıştır. Ölçekleme faktörleri halihazırda var olan hata oranları ile çarpılarak yeni durumdaki hata oranları hesaplanmıştır.
Turkiye Elektrik Iletim Sebekesinde Batarya Enerji Depolama Sistemlerinin Boyutlandrlmas Ve Konumlandrlmas
(2024) Şen, Hatice Hilal; Çulhan Kumcu, Gül; Altın Kayhan, Ayşegül
[No Abstract Available]
Citation - Scopus: 2
Optimal Maintenance Policy for a Markov Deteriorating System Under Reliability Limit
(Polish Maintenance Soc, 2024) Ozturk, Meltem Kocer; Khaniyev, Tahir
In this study, failure data of computer numerical control machine used in defense industry was analyzed to develop maintenance algorithm with a Markov feature. An imperfect preventive maintenance model that minimizes long-term operational cost is created for the machine wearing down randomly over time. The reliability-centric preventive maintenance policy was developed where the system status was monitored instantaneously. The use and age-related deterioration process of system is defined as the failure rate increase factor and age reduction factor, and these variables are combined to create hybrid failure model. As result of the imperfect maintenance algorithm developed for the multi-component machine, minimum long-term total unit cost, optimum system reliability value, number of maintenance and times between sequential maintenance cycles are obtained as outputs. Furthermore, system sub-equipment was specified that needs to be maintained in each cycle. Moreover, imperfect maintenance activities are planned when the reliability level of subsystems drops to the predetermined R value.
Citation - Scopus: 1
Simulation of Migration Paths Using Agent-Based Modeling: the Case of Syrian Refugees En Route To Turkey
(Elsevier Ltd, 2024) Güngör Ö.; Günneç D.; Salman S.; Yücel E.
The decade-long Syrian civil war has triggered a significant migration wave in the Middle East, with Turkey hosting the largest number of Syrian refugees. Our study introduces an agent-based model (ABM) designed to simulate and predict migration paths in potential future refugee crises. The primary goal is to support aid organizations in planning the delivery of essential aid services during migration movements, offering insights that can be applied to various geographical areas and migration scenarios. While we use the Syrian refugee movement to Turkey as a case study, the model is intended as a flexible tool for analyzing migration patterns in future crises. The proposed ABM considers two characteristics of refugee groups: level of risk sensitivity and level of information. To enhance the model's functionality, we have extended the A* algorithm with a cost metric to calculate the weighted average of distance and risk to a destination point. Our case study examines the crisis in southern Idlib through six scenarios, offering insights into refugee numbers, migration paths, camp occupancy rates, and heat maps of densely populated regions for each scenario. Validation is performed by comparing model outcomes with situation reports and official statements from the relevant period, demonstrating the proposed ABM's potential for adaptation to other migration instances and further analysis under different parameters. © 2024 Elsevier Ltd
Citation - Scopus: 2
A Domain-Aware Federated Learning Study for Cnc Tool Wear Estimation
(Springer Science and Business Media Deutschland GmbH, 2024) Kaleli, I.S.; Unal, P.; Deveci, B.U.; Albayrak, O.; Ozbayoglu, Ahmet Murat
This study proposes a cutting tool condition monitoring platform for CNC machines used in metal part manufacturing to estimate tool wear values. The PHM 2010 Dataset, along with operational and situational data from CNC machines and sensors, were analyzed using artificial intelligence algorithms to support total equipment performance with current tool wear values. The innovation lies in developing an artificial intelligence application that incorporates the Federated Learning method with artificial neural networks. This application is among the first to monitor machine cutting tools using Federated Learning. An efficient and accurate predictive tool wear estimation method is presented through the application of Federated Learning with Long-Short Term Memory models. This novel approach holds great potential for industrial applications, optimizing CNC cutting processes and reducing operational costs through enhanced tool wear prediction. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Citation - Scopus: 3
A Novel Differentiated Coverage-Based Lifetime Metric for Wireless Sensor Networks
(Elsevier, 2024) Nurcan-Atceken, Derya; Altın Kayhan, Ayşegül; Tavlı, Bülent
This paper delves into optimizing network lifetime (NL) subject to connected-coverage requirement, a pivotal issue for realistic wireless sensor network (WSN) design. A key challenge in designing WSNs consisting of energy-limited sensors is maximizing NL, the time a network remains functional by providing the desired service quality. To this end, we introduce a novel NL metric addressing target-specific coverage requirements that remedies the shortcomings imposed by conventional definitions like first node die (FND) and last node die (LND). In this context, while we want targets to be sensed by multiple sensors for a portion of the network lifetime, we let the periods, during which cells are monitored by at least one sensor, vary. We also allow the ratios of multiple and single tracking times to differ depending on the target and incorporate target-based prioritization in coverage. Moreover, we address role assignment to sensors and propose a selective target- sensor assignment strategy. As such, we aim to reduce redundant data transmissions and hence overall energy consumption in WSNs. We first propose a unique 0-1 mixed integer programming (MIP) model, to analyze the impact of our proposal on optimal WSN performance, precisely. Next, we present comprehensive comparative studies of WSN performance for alternative NL metrics regarding different coverage requirements and priorities across a wide range of parameters. Our test results reveal that by utilizing our novel NL metric total coverage time can be improved significantly, while facilitating more reliable sensing of the target region.
Citation - Scopus: 10
Capacitated Mobile Facility Location Problem With Mobile Demand: Efficient Relief Aid Provision To En Route Refugees
(Elsevier Ltd, 2024) Pashapour,A.; Günneç,D.; Salman,F.S.; Yücel, Eda
As a humanity crisis, the tragedy of forced displacement entails relief aid distribution efforts among en route refugees to alleviate their migration hardships. This study aims to assist humanitarian organizations in cost-efficiently optimizing the logistics of capacitated mobile facilities utilized to deliver relief aid to transiting refugees in a multi-period setting. The problem is referred to as the Capacitated Mobile Facility Location Problem with Mobile Demands (CMFLP-MD). In CMFLP-MD, refugee groups follow specific paths, and meanwhile, they receive relief aid at least once every fixed number of consecutive periods, maintaining continuity of service. To this end, the overall costs associated with capacitated mobile facilities, including fixed, service provision, and relocation costs, are minimized. We formulate a mixed integer linear programming (MILP) model and propose two solution methods to solve this complex problem: an accelerated Benders decomposition approach as an exact solution method and a matheuristic algorithm that relies on an enhanced fix-and-optimize agenda. We evaluate our methodologies by designing realistic instances based on the Honduras migration crisis that commenced in 2018. Our numerical results reveal that the accelerated Benders decomposition excels MILP with a 46% run time improvement on average while acquiring solutions at least as good as the MILP across all instances. Moreover, our matheuristic acquires high-quality solutions with a 2.4% average gap compared to best-incumbents rapidly. An in-depth exploration of the solution properties underscores the robustness of our relief distribution plans under varying migration circumstances. Across several metrics, our sensitivity analyses also highlight the managerial advantages of implementing CMFLP-MD solutions. © 2024 Elsevier Ltd
Asymptotic Expansions for the Stationary Moments of a Modified Renewal-Reward Process With Dependent Components
(Pleiades Publishing, 2024) Poladova,A.; Tekin, Salih; Khaniyev, Tahir
Abstract: In this paper, a modification of a renewal-reward process with dependent components is mathematically constructed and the stationary characteristics of this process are studied. Stochastic processes with dependent components have rarely been studied in the literature owing to their complex mathematical structure. We partially fill the gap by studying the effect of the dependence assumption on the stationary properties of the process. To this end, first, we obtain explicit formulas for the ergodic distribution and the stationary moments of the process. Then we analyze the asymptotic behavior of the stationary moments of the process by using the basic results of the renewal theory and the Laplace transform method. Based on the analysis, we obtain two-term asymptotic expansions of the stationary moments. Moreover, we present two-term asymptotic expansions for the expectation, variance, and standard deviation of the process. Finally, the asymptotic results obtained are examined in special cases. © Pleiades Publishing, Ltd. 2024.
Citation - Scopus: 1
Obtaining a Multi-Factor Optimum Blend Using Scrap Within the Scope of Sustainable and Environmentally Friendly Steel Production: Application in a Steel-Casting Company
(Mdpi, 2024) Baş, Aydoğan; Birgören, Burak; Sakallı Umit Sami
This study tackles the challenge of optimizing scrap blends in steel production to achieve sustainability and environmental consciousness. Focusing on a steel-casting company as a case study, we develop a mathematical model that minimizes cost, emissions, and energy consumption while maximizing scrap utilization. This model considers the specific elemental composition of various scrap piles and pure elements, alongside their associated costs and environmental impacts in the production of GS52 steel in a foundry company. Through the GAMS program and further verification with Microsoft Excel, we demonstrate that the optimal blend significantly reduces raw material costs by prioritizing scrap (99.7%) over pure elements. Moreover, this optimized blend minimizes energy consumption and associated carbon emissions, thus contributing to a more sustainable and environmentally friendly steel production process. This study offers valuable insights and a practical framework for the steel industry to adopt cost-effective and eco-conscious practices, aligning with global efforts towards sustainable manufacturing.
Citation - Scopus: 4
Fair and Effective Vaccine Allocation During a Pandemic
(Elsevier Ltd, 2024) Erdoğan, G.; Yücel, E.; Kiavash, P.; Salman, F.S.
This paper presents a novel model for the Vaccine Allocation Problem (VAP), which aims to allocate the available vaccines to population locations over multiple periods during a pandemic. We model the disease progression and the impact of vaccination on the spread of the disease and mortality to minimise total expected mortality and location inequity in terms of mortality ratios under total vaccine supply and hospital and vaccination centre capacity limitations at the locations. The spread of the disease is modelled through an extension of the well-established Susceptible–Infected–Recovered (SIR) epidemiological model that accounts for multiple vaccine doses. The VAP is modelled as a nonlinear mixed-integer programming model and solved to optimality using the Gurobi solver. A set of scenarios with parameters regarding the COVID-19 pandemic in the UK over 12 weeks are constructed using a hypercube experimental design on varying disease spread, vaccine availability, hospital capacity, and vaccination capacity factors. The results indicate the statistical significance of vaccine availability and the parameters regarding the spread of the disease. © 2024 Elsevier Ltd
Citation - Scopus: 6
The Home Health Care Routing With Heterogeneous Electric Vehicles and Synchronization
(Springer, 2024) Cebeci, Eşref; Yücel, Eda; Koc, Çağrı
This paper studies the problem of heterogeneous electric vehicles, fast chargers, and synchronized jobs that have time windows in home healthcare routing and scheduling. We consider a problem that aims to establish daily routes and schedules for healthcare nurses to provide a variety of services to patients located in a scattered area. Each nurse should be assigned to an electric vehicle (EV) from a heterogeneous fleet of EVs to perform the assigned jobs within working hours. We consider three different types of EVs in terms of battery capacity and energy consumption. We aim to minimize the total cost of energy consumption, fixed nurse cost, and costs arising from the patients that cannot be served within the working day. We model the problem as a mixed integer programming formulation. We develop a hybrid metaheuristic based on a greedy random adaptive search procedure heuristic, to generate good quality initial solutions quickly, and an adaptive variable neighborhood search algorithm to generate high quality solutions in reasonable time. The hybrid metaheuristic employs a set of new advanced efficient procedures designed to handle the complex structure of the problem. Through extensive computational experiments, the performance of the mathematical model and the hybrid metaheuristic are evaluated. We conduct analyses on the robustness of the metaheuristic and the performance contribution of employing adaptive probabilities. We analyze the impact of problem parameters such as competency requirements, job duration, and synchronized jobs.
Energy Efficient Ceramic Sanitaryware Production Planning With a Hybrid Simulation Optimization Method
(IEOM Society International, 2022) Doğru, Emre; Fescioğlu Ünver, Nilgün
The ceramic sanitaryware production process consists of casting, drying, glazing, and firing operations. The operation that uses the most energy is the firing process. This study handles a case sanitaryware production factory and proposes a production planning method for energy-efficient manufacturing. In the case factory, the firing process takes place on wagons that carry the products through a tunnel-gas oven. Increasing the wagon surface area utilization decreases the energy consumption per unit product. The wagons continuously move with a predetermined speed and pick up their loads from the end of the glazing lines. The glazing lines have limited-sized end buffers, and products are manually carried in case of a buffer overflow. A wagon can load a product only if the product is ready in the glazing line end buffer while the wagon is passing in front of that line in real-time. Efficient wagon loading requires having the right products at the end buffers at the right time. This study develops a hybrid simulation optimization model to determine the production plan that minimizes the number of wagons used and the buffer overflows. The proposed method consists of two parts. The first part uses a linear programming model to assign the product demands to appropriate glazing lines such that the glazing lines' workload is balanced in terms of total production time and total product surface in lines. Then the model orders the products in each line according to their types and assigns them to drying process vehicles. The second part of the model uses a hybrid simulation - genetic algorithm heuristic to obtain the best product/wagon assignments with the given glazing production plan. The production plan is further improved with a heuristic drying vehicle replacement rule. The model gradually improves the production plan within a closedloop cycle between the wagon-product assignment heuristic and the drying vehicle replacement heuristic. Results show that the model can effectively reduce the number of wagons used and buffer overflow for a given demand.
Investigation of Random Walk Process With Two Barriers and Triangular Interference of Chance
(Ministry of Digital Development and Transport of Azerbaijan Republic, 2022) Jafarova, H.; Hanalioglu, Z.; Khaniyev, T.
In this work the process which can be called as “random walk process with two barriers and triangular interference of chance’ is investigated. The main goal of this study is to investigate of the limiting form of the characteristic functions of the ergodic distribution of the processes.
Prediction of Migration Paths Using Agent-Based Simulation Modeling: the Case of Syria
(IEOM Society International, 2022) Güngör, Özlem; Günneç, Dilek; Salman, F. Sibel; Yücel, Eda
The Syrian civil war, which started in 2011, has caused a great wave of forced migration in the Middle East. One of the most popular destination points for Syrian refugees has been Turkey. The purpose of this study is to predict the routes of refugees who leave the conflict areas in Syria to reach the refugee camps located in Turkey during a crisis. The study proposes an agent-based model to simulate the decision mechanisms of refugees in a highly uncertain environment. The model employs the A* algorithm to calculate the cost of each available destination point (refugee camp) for each agent, based on their risk preferences and starting locations, and allows agents to choose the camp with the minimum cost as the destination point. By use of the model, we simulate a moment of crisis namely the South Idlib bombardment (from December 2019 to January 2020) under four different scenarios that are generated considering the real-life data gathered from the newspapers of December 2019 and various other sources. The simulation results show the main pathways of Syrian refugees and give insights on the required camp capacities. The results are compared with the gathered secondary data to validate the proposed model.
Citation - Scopus: 1
Quality Driven Maintenance Policies for a Deteriorating System Subject To Non-Self Failures
(Taylor & Francis Inc, 2024) Bakir, Niyazi Onur; Keleş, Büşra; Tekin, Salih
In this study, we develop condition-based maintenance policies for a multi-state system subject to continuous-time Markovian deterioration that can result in non-self-announcing degradation including failure. Periodic inspections reveal the true state of the system; good, medium, poor, or failed. Upon receiving this piece of information, one of do-nothing, minor repair, major repair, fix repair, or replace maintenance actions is taken. On one hand, the system brings monetary rewards commensurate with system state-different rewards are earned per unit time spent in different states. On the other hand, quality loss that results from degraded system state is converted into monetary units-inspection and maintenance costs. Therefore, our objective is to determine the optimum inspection period and the corresponding maintenance policy that maximizes the expected long-run profit rate. We provide numerical examples to conduct sensitivity of the optimum inspection period and policy to system parameters, and to present the practical utility of our results.
Citation - Scopus: 6
A Multi-Objective Perspective To Satellite Design and Reliability Optimization
(Elsevier Ltd, 2024) Tetik, T.; Sena, Daş, G.; Birgoren, B.
Development of a communication satellite project is highly complicated and expensive which costs a few hundred million dollars depending on the mission in space. Once a satellite is launched into orbit, it has to operate in harsh environmental conditions including radiation, solar activity, meteorites, and extreme weather patterns. Since there is no possibility of physical maintenance intervention in space, reliability is a critical attribute for all space and satellite projects. Therefore, the redundancy philosophy and reliability measures are taken into account in the design phase of a satellite to prevent the loss of functionality in case of a failure in orbit. This study aims to optimize the payload design of a communication satellite by considering the system's reliability, power consumption and cost simultaneously. Since these objectives are conflicting in their nature, a multi-objective optimization approach is proposed. We offer a systematic approach to the satellite design by determining the best redundancy strategy considering contradictory objectives and onboard constraints in the multibillion-dollar satellite industry. The proposed approach promotes trade-offs and sensitivity analyses between cost, power consumption and system reliability in the early design phase of satellites using Compromise Programming. By using different sets of weights for the objectives in our model, it is possible to address different types of satellites depending on their mission and priorities. Because of the NP-Hard characteristics of the reliability optimization problem and the nonlinear equation in the proposed model, the Simulated Annealing algorithm is utilized to solve the problem. As a case analysis, the implementation is carried out on the design of a communication satellite system with active hot-standby and warm-standby onboard redundancy schemes. Results reveal that huge savings in million dollars can be attained as a result of approximately 5% reduction in reliability. © 2024 Elsevier Ltd
Investigation of Upper Bound for the Ruin Probability by Approximate Methods in a Nonlinear Risk Model With Gamma Claims
(Institute of Electrical and Electronics Engineers Inc., 2023) Khaniyev, T.; Gever, B.; Hanalioglu, Z.
This study considers a non-linear Cramér-Lundberg model of the risk theory and investigates the adjustment coefficient when the claims have gamma distribution. The ruin probability of this non-linear risk model is considered when the premium function is square root of time. Thus, in this study, the adjustment coefficient is explored by numerical methods and proposed an approximate formula for practical calculation of adjustment coefficient. Moreover, an implementation of the obtained approximate formula, which investigates ruin probability, is included as an example at the end of the paper. © 2023 IEEE.
Citation - Scopus: 43
Electric Vehicle Charging Service Operations: a Review of Machine Learning Applications for Infrastructure Planning, Control, Pricing and Routing
(Elsevier Ltd, 2023) Fescioğlu Ünver, Nilgün; Yıldız, Aktaş, M.
The majority of global road transportation emissions come from passenger and freight vehicles. Electric vehicles (EV) provide a sustainable transportation way, but customers’ charging service related concerns affect the EV adoption rate. Effective infrastructure planning, charge scheduling, charge pricing, and electric vehicle routing strategies can help relieve customer perceived risks. The number of studies using machine learning algorithms to solve these problems is increasing daily. Forecasting, clustering, and reinforcement based models are frequently the main solution methods or provide valuable inputs to other solution procedures. This study reviews the studies that apply machine learning models to improve EV charging service operations and provides future research directions. © 2023 Elsevier Ltd
Citation - Scopus: 2
Moment-Based Approximations for Stochastic Control Model of Type (s, S)
(Taylor & Francis Inc, 2023) Kamislik, Asli Bektas; Baghezze, Feyrouz; Kesemen, Tulay; Khaniyev, Tahir
In this study, we propose an approximation for a renewal reward process that describes a stochastic control model of type (s, S) based on the first three moments of demand random variables. Various asymptotic expansions for this model exist in the literature. All these studies rely on the condition of knowing the distribution function of demand random variables and require obtaining the asymptotic expansion of the renewal function produced by them. However, obtaining a renewal function can be challenging for certain distribution families, and in some cases, the mathematical structure of the renewal function is difficult to apply. Therefore, in this study, simple and compact approximations are presented for the stochastic control model of type (s, S). The findings of this study rely on Kambo's method, through which we obtain approximations for the ergodic distribution, and the nth order ergodic moments of this process. To conclude the study, the accuracy of the proposed approximate formulas are examined through a specialized illustrative example. Moreover, it has been noted that the proposed approximation is more accurate than the approximations existing in the literature.
Citation - Scopus: 1
MODELING DISEASE TRANSMISSION DYNAMICS WITH RANDOM DATA AND HEAVY TAILED RANDOM EFFECTS: THE ZIKA CASE
(Isik University, 2023) Bekiryazici, Z.; Kesemen, T.; Merdan, M.; Khaniyev, T.
In this study, we investigate a compartmental model of Zika Virus transmission under random effects. Random effects enable the analysis of random numerical characteristics of transmission, which cannot be modeled through deterministic equations. Data obtained from Zika studies in the literature are used along with heavy tailed random effects to obtain new random variables for the parameters of the deterministic model. Finally, simulations of the model are carried out to analyze the random dynamics of Zika Virus transmission. Deterministic results are compared with results from the simulations of the random system to underline the advantages of a random modeling approach. It is shown that the random model provides additional results for disease transmission dynamics such as results for standard deviation and coefficients of variation, making it a valuable alternative to deterministic modeling. Random results suggest around 90% - 120% coefficient of variation for the random model underlining the fact that the randomness should not be ignored for the transmission of this disease. © Işık University, Department of Mathematics, 2023; all rights reserved.

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