Endüstri Mühendisliği Bölümü / Department of Industrial EngineeringEndüstri Mühendisliği Bölümüne ait koleksiyonları listeler.https://hdl.handle.net/11729/412024-03-28T15:56:31Z2024-03-28T15:56:31ZMaintenance policy analysis of the regenerative air heater system using factored POMDPsKıvanç, İpekÖzgür Ünlüakın, DemetBilgiç, Tanerhttps://hdl.handle.net/11729/33702024-03-26T16:18:44Z2022-03-01T00:00:00ZMaintenance policy analysis of the regenerative air heater system using factored POMDPs
Kıvanç, İpek; Özgür Ünlüakın, Demet; Bilgiç, Taner
Maintenance optimization of multi-component systems is a difficult problem. Partially Observable Markov Decision Processes (POMDPs) are powerful tools for such problems under uncertainty in stochastic environments. In this study, the main POMDP solution approaches and solvers are surveyed. Then, based on experimental models with different complexities in the size of the system space, selected POMDP solvers using different representation patterns for modeling and different procedures for updating the value function while solving are compared. Furthermore, to show that factored representations are advantageous in modeling and solving the maintenance problem of multi-component systems where there exist also stochastic dependencies among the components, the maintenance problem of the one-line regenerative air heater system available in thermal power plants is modeled and solved with factored POMDPs. In-depth sensitivity analyses are performed on the obtained policy. The results show that factored POMDPs enable compact modeling, efficient policy generation and practical policy analysis for the tackled problem. Furthermore, they also motivate the use of factored POMDPs in the generation and analysis of maintenance policies for similar multi-component systems.
2022-03-01T00:00:00ZChallenges in the CO2 emissions of the Turkish power sector: Evidence from a two-level decomposition approachIşık, MineAri, İzzetSarıca, Kemalhttps://hdl.handle.net/11729/31472024-01-24T22:09:07Z2021-06-01T00:00:00ZChallenges in the CO2 emissions of the Turkish power sector: Evidence from a two-level decomposition approach
Işık, Mine; Ari, İzzet; Sarıca, Kemal
Decarbonization of the energy system is urgent to avert the disruptions in the climate. Considering its share, the low carbon transition of the power sector is pivotal. Growing electricity demand poses unique challenges for Turkey to enact deep decarbonization. It is vital to uncover the contributing causes of emissions to provide strategic oversight for carbon management activities. This study investigates key drivers of CO2 emissions from the power sector using the Logarithmic Mean Divisia Index decomposition method. While efficiency improvement contributes to sustainable yet minor mitigation, changes in the fossil-fuel share indicate a cycling but significant overall impact.
2021-06-01T00:00:00ZEvaluation of proactive maintenance policies on a stochastically dependent hidden multi-component system using DBNsÖzgür Ünlüakın, DemetTürkali, Busenurhttps://hdl.handle.net/11729/31052024-01-24T23:02:53Z2021-07-01T00:00:00ZEvaluation of proactive maintenance policies on a stochastically dependent hidden multi-component system using DBNs
Özgür Ünlüakın, Demet; Türkali, Busenur
In complex systems with stochastically dependent components which are not observed directly, determining an effective maintenance policy is a difficult task. In this paper, a dynamic Bayesian network based maintenance decision framework is proposed to evaluate proactive maintenance policies for such systems. Two preventive and one predictive maintenance strategies from a cost perspective are designed for multi-component dependable systems which aim to reduce maintenance cost while increasing system reliability at the same time. Tabu procedure is employed to avoid repetitive similar actions. The performances of the policies are compared with a reactive maintenance strategy and also with each other using different strategy parameters on a real life system confronted in thermal power plants for six different scenarios. The scenarios are designed considering different structures of system dependability and reactive cost. The results show that the threshold based maintenance which is the predictive strategy gives the minimum cost and maintenance number in almost all scenarios.
This research is supported by the Scientific and Technological Research Council of Turkey (TUBITAK) under grant: 117M587.
2021-07-01T00:00:00ZScheduling and simulation of maritime traffic in congested waterways: An application to the Strait of IstanbulÖzlem, ŞirinOr, İlhanAltan, Yiǧit Canhttps://hdl.handle.net/11729/30782024-01-24T23:34:57Z2021-05-01T00:00:00ZScheduling and simulation of maritime traffic in congested waterways: An application to the Strait of Istanbul
Özlem, Şirin; Or, İlhan; Altan, Yiǧit Can
The aim of this study is to develop a simulation model which is capable of mimicking actual vessel arrival patterns and vessel entrance decisions (which are made based on expert opinions generally) on congested, narrow waterways. The model is tested on the transit traffic pattern in the Strait of Istanbul. Based on a heuristic scheduling algorithm, this model decides entrance times and vessel types on the strait. The model, with different policies for day and night traffic, is run for a period of seven years with 20 replications for each year. The performance measures of the model are: average interarrival times, number of vessels passed and entrance times for each successive vessel pair in both traffic directions. The model results are congruent with the actual results of performance measures. Therefore, it may be deduced that the proposed algorithm can be a guide for operators regarding scheduling decisions in congested, narrow waterways.
This work was supported by the Scientific and Technological Research Council of Turkey, TUBITAK BIDEB [2211-A].
2021-05-01T00:00:00Z