Ticari Bilimler Fakültesi / Faculty of Commercial Science
Permanent URI for this collectionhttps://hdl.handle.net/11727/2074
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Item Sustainable personnel scheduling supported by an artificial neural network model in a natural gas combined cycle power plant(2020) Ozder, Emir Huseyin; Ozcan, Evrencan; Eren, Tamer; 0000-0002-1895-8060; Q-4772-2017Despite the impact of personnel scheduling on the sustainability of production processes, it is a rarely studied problem in the electricity generation sector, whose main purpose is sustainable energy generation. From this point of view, personnel scheduling problem is handled in this study based on the impact of this problem, which focuses on fair and balanced job distribution according to the personnel qualifications, on the sustainable generation in the power plants. With its advantages such as ease of operation and maintenance, fast commissioning, lower greenhouse gas emissions compared to other fossil fuels and etc. one of the biggest Natural Gas Combined Cycle Power Plant (NGCCPP) in Turkey is chosen as application area. The main purpose of the study is to demonstrate the effect of fair, balanced and competency-based personnel scheduling on generation stoppages resulting from personnel planning in power plants, which have great importance in energy supply security of the countries. This study is the first in the literature in terms of three different aspects. Firstly, in the energy sector, it is different in that it is a personnel scheduling study that takes into consideration the job assignment of the personnel according to their abilities and minimizes costs. Secondly, the large size of the problem is different from that of previous studies in the literature. Finally, the number of personnel employed in this generation facility varies according to the season. At this point, the past generation data are analyzed using an Artificial Neural Network (ANN) method and an estimation is made, and personnel scheduling is performed in the light of this information. Consequently, the proposed multi-objective mathematical model supported with multi-criteria decision making and ANN, shutdown rate of the power plant due to operator error is reduced 67.3%, and personnel satisfaction level is increased from 42% to 89%as solution.Item A Systematic Literature Review for Personnel Scheduling Problems(2020) Ozder, Emir Huseyin; Ozcan, Evrencan; Eren, Tamer; 0000-0002-1895-8060; Q-4772-2017Organizations need to focus on many parameters to reach their goals such as personnel satisfaction at the top level, profit maximization, increasing system efficiency and minimizing costs. By carefully examining the significant effect of personnel scheduling on the production of goods and services, achieving a fair distribution of work among the employees paves the way for higher motivation and performance of the employees, particularly, in production and service industries. In this paper, a systematic literature review (SLR) approach is used to demonstrate the necessity of scheduling studies in order to overcome the deficiencies in auxiliary activity groups. It sheds light on a new and very important areas such as examining the model structures of sector differences, and guiding researchers. New trends and approaches are presented for the personnel scheduling problems. Different classification perspectives are displayed.Item Staff Task-Based Shift Scheduling Solution with an ANP and Goal Programming Method in a Natural Gas Combined Cycle Power Plant(2019) Ozder, Emir Huseyin; Ozcan, Evrencan; Eren, Tamer; 0000-0002-1895-8060; Q-4772-2017Shift scheduling problems (SSPs) are advanced NP-hard problems which are generally evaluated with integer programming. This study presents an applicable shift schedule of workers in a large-scale natural gas combined cycle power plant (NGCCPP), which realize 35.17% of the total electricity generation in Turkey alone, as at of the end of 2018. This study included 80 workers who worked three shifts in the selected NGCCPP for 30 days. The proposed scheduling model was solved according to the skills of the workers, and there were nine criteria by which the workers were evaluated for their abilities. Analytic network process (ANP) is a method used for obtaining the weights of workers' abilities in a particular skill. These weights are used in the proposed scheduling model as concepts in goal programming (GP). The SSP-ANP-GP model sees employees' everyday preferences as their main feature, bringing high-performance to the highest level, and bringing an objective functionality, and lowering the lowest success of daily choice. At the same time, the model introduced large-scale and soft constraints that reflect the nature of the shift requirements of this program by specifying the most appropriate program. The required data were obtained from the selected NGCCPP and the model solutions were approved by the plant experts. The SSP-ANP-GP model was resolved at a reasonable time. Monthly acquisition time was significantly reduced, and the satisfaction of the employees was significantly increased by using the obtained program. When past studies were examined, it was determined that a shift scheduling problem of this size in the energy sector had not previously been studied.Item Sustainable Personnel Scheduling Problem Optimization in a Natural Gas Combined-Cycle Power Plant(2019) Ozder, Emir Huseyin; Ozcan, Evrencan; Eren, Tamer; 0000-0002-1895-8060; Q-4772-2017This paper deals with a sustainable personnel scheduling problem of personnel working in a large-scale natural gas combined-cycle power plant in Turkey. The proposed model focuses on employee complaints due to unfair work schedules and the results of balanced assignments based on power plant interruptions. Eighty personnel work in three shifts at this natural gas combined-cycle power plant. The model is solved with respect to some of the workers' skills, and there are 20 criteria regarding skills. The analytic network process method is used to get the weights of workers' skills, which are calculated and included in the model. Goal programming is used in this paper. Our proposed model gives cost minimization and fair work schedules for the power plant. Compared with the literature, the number and set of criteria are unique in terms of personnel competency in the energy sector. Minimizing cost and imbalanced assignments was achieved by the proposed model for the first time without considering the sector.