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변동성 기반 대기행렬 이론을 이용한 조선 생산계획 및 조달계획 데이터 분석
곽동훈(Dong Hoon Kwak),유상현(Sang Hyeon Yu),우종훈(Jong Hun Woo),박중구(Jung Goo Park) 대한산업공학회 2020 대한산업공학회지 Vol.46 No.6
In order to establish an accurate production plan, the net working time must be determined in consideration of unit working time and production volume, then the production time must be determined in consideration of the appropriate allowance time with the net working time. However, since the unit working time of shipbuilding is inaccurate and there are many difficulties in calculating the production volume, most shipyards are following the top-down procedure based on the past ship’s production records. In addition, shipyards have very large variability affecting production time, such as delay and waiting, because human factors dominate. Nevertheless, there has been little scientific analysis of this variability. Variability is a kind of statistical variable. When applied to a production system in combination with the queuing theory, it is possible to analyze the production process through scientific analysis and draw productivity improvement because it is possible to analyze the variability considering production time and process capability. Researches on variability have been applied to mass production industries such as automobile production. The target of most researches of variability in the mass production industry is to reduce the variability of production time to secure higher productivity with the given production resources. However, in the case of the shipbuilding industry, the variability in production time is very high and difficult to control compared to the mass production industry. So, queuing analysis with high variability never has been studied in shipbuilding. In this study, the quantitative variability level of the shipbuilding of Korea is investigated through the queuing analysis with variability with respect to the schedule and procurement plan of the shipyard, and the scientific analysis is conducted for the analysis of the relationship between the productivity and the composition of shipyard production resources.
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조영인(Young-In Cho),오승헌(Seung-Heon Oh),곽동훈(Dong-Hoon Kwak),최재호(Jae-Ho Choi),우종훈(Jong Hun Woo) (사)한국CDE학회 2022 한국CDE학회 논문집 Vol.27 No.2
In the shipbuilding, outfitting processes are mainly performed on ships moored by quays of the shipyard. Quays in shipyards have different lengths, depths, and facilities so that the allowable quays for each ship are limited. In addition, the working efficiency of the quay process depends on the kinds of the quays where the outfitting processes are performed. As a result, it is inevitable for ships to move around the quays to avoid delay in schedule while maximizing the working efficiency. The movements of ships should be minimized because it is a waste of cost and time. In most shipyards, the quay allocation is manually determined by planners using their own implicit rules. However, the optimal plan can’t be obtained by those heuristics which only considers limited problem space. In this study, the scheduling algorithm for the quay allocation problem is developed using a reinforcement learning approach. Based on the Markov decision process model using discrete-event simulation, the scheduling agent is trained by DRQN (Deep Recurrent Q-network) algorithm and tested with 10 scenarios. The proposed algorithm outperforms the reference value set by heuristic in terms of three KPIs-unallocated duration, the number of ship movements, and ship-quay priority ratio.
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