의사결정트리 학습을 적용한 조선소 블록 적치 위치 선정에 관한 연구
A Study on Selection of Block Stockyard Applying Decision Tree Learning Algorithm
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초록
It is very important to manage the position of the blocks in the shipyard where the work is completed, or the blocks need to be moved for the next process operation. The moving distance of the block increases according to the position of the block stockyard. As the travel distance increases, the number of trips and travel distance of the transporter increases, which causes a great deal of operation cost. Currently, the selection of the block position in the shipyard is based on the know-how of picking up a transporter worker by the production schedule of the block, and the location where the block is to be placed is determined according to the situation in the stockyard. The know-how to select the position of the block is the result of optimizing the position of the block in the shipyard for a long time. In this study, we used the accumulated data as a result of the operation of the yard in the shipyard and tried to select the location of blocks by learning it. Decision tree learning algorithm was used for learning, and a prototype was developed using it. Finally, we prove the possibility of selecting a block stockyard through this algorithm.
Abstract
It is very important to manage the position of the blocks in the shipyard where the work is completed, or the blocks need to be moved for the next process operation. The moving distance of the block increases according to the position of the block stockyard. As the travel distance increases, the number of trips and travel distance of the transporter increases, which causes a great deal of operation cost. Currently, the selection of the block position in the shipyard is based on the know-how of picking up a transporter worker by the production schedule of the block, and the location where the block is to be placed is determined according to the situation in the stockyard. The know-how to select the position of the block is the result of optimizing the position of the block in the shipyard for a long time. In this study, we used the accumulated data as a result of the operation of the yard in the shipyard and tried to select the location of blocks by learning it. Decision tree learning algorithm was used for learning, and a prototype was developed using it. Finally, we prove the possibility of selecting a block stockyard through this algorithm.
참고문헌 (18)
- Breiman, L., "Classification and regression trees" (1984), Wadsworth and Books
- Cho, K.K., "A spatial scheduling system for block painting process in shipbuilding", The International Academy for Production Engineering, CIRP Annals-Manufacturing Technology, 50(1), pp.339~342 (2001)
- Hartigan, J. A., "Clustering algorithms" (1975), John Wiley & Sons
- Jang, B. T., "Next-generation machine learning technology", 25(3), pp.96~107 (2007), Communications of the Korean Institute of Information Scientists and Engineers
- 정영수, "조선소의 블록 운반 관리 시스템", 석사, Mechatronics, pp.IT, 2007
- Kim, M.S, "Determination of arrangement and take-out path in ship block stockyard considering available space and obstructive block", Proceedings of the Society of CAD, 2013, ~
- Kim, J.O., "Development of real time location measuring and logistics system for assembled block in shipbuiling", 2009 Conference on Korean Operations Research And Management Society (2009)
- Koh, S. G., "A production schedule with genetic algorithm in block assembly shop", Korean Management Science Review, 13(1), pp.1~12 (1996)
- 이종무, "대형 조선소의 생산 계획 통합 프로세스 및 평가 프레임워크 연구", 박사, 조선해양공학, pp.2007
- Lee, K.H., "A study on the data analysis and utilization method based on datamining concept in ship design", 2005 Conference of Society for Computer Aided Design and Computer Aided Engineering (2005)
- Lee, K.J., "A spatial scheduling system and its application to shipbuilding DAS-CURVE", Expert Systems With Applications, 10(3, pp.4) (1996), 311~324
- 이상협, "조선 야드에서의 블록 운반 계획", 박사, 산업공학, pp.2011
- Lee, Y.H., "Study on the positioning system for logistics of ship-block", Special Issue of the Society of Naval Acrchitects of Korea, pp.68~75 (2008)
- 박창규, "조립블록 지번할당 알고리즘 개발: 현대중공업 사례", 산업공학(IE interfaces), 19(2), pp.160~167 (2006), 대한산업공학회
- Park, M.H., "A review of Korean shipbuilding industry and engineering research", Industrial Engineers Interfaces, 8(2), pp.5~20 (1995)
- Roh, M. I., "Block layout method in the block stockyard based on the genetic algorithm", Ocean Systems Engineering, 2(4), pp.271~287 (2012)
- 손정열, "조선 산업의 블록 적치장 운영계획 휴리스틱알고리즘", 대한조선학회 논문집, 51(3), pp.239~245 (2014), 대한조선학회
- Quinlan, J.R, "Programs for machine learning" (1993), Morgan Kaufmann Publishers