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Citation:
　Gunawan,Kunihiro Hamada,Kakeru Kunihiro,et al.Automated Pipe Routing Optimization for Ship Machinery[J].Journal of Marine Science and Application,2022,(2):170-178.[doi:10.1007/s11804-022-00269-8]
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Automated Pipe Routing Optimization for Ship Machinery

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Title:
Automated Pipe Routing Optimization for Ship Machinery
Author(s):
Gunawan1;  Kunihiro Hamada2;  Kakeru Kunihiro2;  Allessandro Setyo Anggito Utomo1;  Michael Ahli1;  Raymond Lesmana1;  Cornelius1;  Yutaka Kobayashi3;  Tadashi Yoshimoto3;  Takanobu Shimizu3
Affilations:
Author(s):
Gunawan1;  Kunihiro Hamada2;  Kakeru Kunihiro2;  Allessandro Setyo Anggito Utomo1;  Michael Ahli1;  Raymond Lesmana1;  Cornelius1;  Yutaka Kobayashi3;  Tadashi Yoshimoto3;  Takanobu Shimizu3
1. Department of Mechanical Engineering, Universitas Indonesia, Kampus UI, Depok, 16424, Indonesia;
2. Graduate School of Engineering, Hiroshima University, 1-4-1 Kagamiyama, Higashi-Hiroshima City, Hiroshima, 739-8527, Japan;
3. Tsuneishi Shipbuilding Co., Ltd., 1083, Tsuneishi, Numakuma-cho, Fukuyama City, Hiroshima, 720-0393, Japan
Keywords:
Design optimization|Piping system|Dijkstra’s algorithm|Shortest path
分类号:
-
DOI:
10.1007/s11804-022-00269-8
Abstract:
In the shipbuilding industry, market competition is currently operating in an intense state. To be able to strive in the global market, the shipbuilders must able to produce ships that are more efficient and can be constructed in a relatively short amount of time. The piping layouts in the engine room requires a lot of time for the designer to design the best possible route and in a way are not the most efficient route. This paper presents an automatic piping support system in the ship’s engine room based on the Dijkstra’s algorithm of pathfinding method. The proposed method is focused on finding the shortest possible route with a consideration of the following things:cost of the bend pipe, cost of the crossing pipe, cost reduction by pipe support, restriction on piping, reduction of calculation time, and design procedure of piping route. Dijkstra’s shortest path algorithm is adopted to find the shortest path route between the start and goal point that is determined based on the layout of the ship’s engine room. Genetic algorithm is adopted to decide the sequence of the pipe execution. The details of the proposed method are explained in this paper. This paper also discusses the application of the proposed method on an actual ship and evaluates its effectiveness.

References:

Ajiwaskita F, Gunawan, Yanuar (2020) Pipe-routing optimization using system engineering methodology in ship engine room. Recent Progress on:Mechanical, Infrastructure and Industrial Engineering. Proceedings of International Symposium on Advances in Mechanical Engineering (ISAME):Quality in Research 2019. https://doi.org/10.1063/5.0001001
Ando Y, Kimura H (2012) An automatic piping algorithm including elbows and bends. Journal of the Japan Society of Naval Architects and Ocean Engineers 15(0):219-226. https://doi.org/10.2534/jjasnaoe.15.219
Bodenhofer U (1999) Genetic Algorithms:Theory and Applications.
Christodoulou S, Ellinas G (2010) Pipe routing through ant colony optimization. Journal of Infrastructure Systems 16(2):149-159. https://doi.org/10.1061/(asce)1076-0342(2010)16:2(149)
Cignoni P, Montani C, Scopigno R (1998) A comparison of mesh simplification algorithms. Computers&Graphics 22(1):37-54. https://doi.org/10.1016/s0097-8493(97)00082-4
Dijkstra E (1959) A note on two problems in connexion with graphs. Numerische Mathematik, 1(1):269-271. https://doi.org/10.1007/bf01386390
Dong Z, Lin Y (2017a) A particle swarm optimization based approach for ship pipe route design. International Shipbuilding Progress 63(1-2):59-84. https://doi.org/10.3233/isp-160123
Dong Z, Lin Y (2017b) Ship pipe routing method based on genetic algorithm and cooperative coevolution. Journal of Ship Production and Design 33(2):122-134. https://doi.org/10.5957/jspd.33.2.150005
Fan Xiaoning, Lin Yan, Ji Zhuoshang (2006) The ant colony optimization for ship pipe route design in 3D space. 20066th World Congress on Intelligent Control and Automation. https://doi.org/10.1109/wcica.2006.1712938
Holland J (1975) Adaptation in Natural and Artificial Systems. Cambridge, Mass:MIT Press, 317-333
Ikehira S, Kimura H, Ikezaki E, Kajiwara H (2005) Automatic design for pipe arrangement using multi-objective genetic algorithms. Journal of the Japan Society of Naval Architects and Ocean Engineers 2(0):155-160. https://doi.org/10.2534/jjasnaoe.2.155
Ito T (1999) A genetic algorithm approach to piping route path planning. Journal of Intelligent Manufacturing, 10(1):103-114. https://doi.org/10.1023/a:1008924832167
Jiang W, Lin Y, Chen M, Yu Y (2015) A co-evolutionary improved multi-ant colony optimization for ship multiple and branch pipe route design. Ocean Engineering 102:63-70. https://doi.org/10.1016/j.oceaneng.2015.04.028
Kanemoto Y, Sugawara R, Ohmura M (2004) A genetic algorithm for the rectilinear Steiner tree in 3-D VLSI layout design. The 200447Th Midwest Symposium on Circuits and Systems 2004. MWSCAS’04. https://doi.org/10.1109/mwscas.2004.1354028
Kang J, Lee B (2017) Optimisation of pipeline route in the presence of obstacles based on a least cost path algorithm and Laplacian smoothing. International Journal of Naval Architecture and Ocean Engineering 9(5):492-498. https://doi.org/10.1016/j.ijnaoe.2017.02.001
Kim D, Corne D, Ross P (1996) Industrial plant pipe-route optimisation with genetic algorithms. Parallel Problem Solving From Nature-PPSN IV, 1012-1021. https://doi.org/10.1007/3-540-61723-x_1064
Liu Q, Wang C (2008) A modified particle swarm optimizer for pipe route design. 200811th IEEE International Conference on Computational Science and Engineering-Workshops. https://doi.org/10.1109/csew.2008.29
Liu Q, Wang C (2011) A discrete particle swarm optimization algorithm for rectilinear branch pipe routing. Assembly Automation 31(4):363-368. https://doi.org/10.1108/01445151111172952
McCall J (2005) Genetic algorithms for modelling and optimisation. Journal Of Computational and Applied Mathematics 184(1):205-222. https://doi.org/10.1016/j.cam.2004.07.034
Min J, Ruy W, Park C (2020) Faster pipe auto-routing using improved jump point search. International Journal of Naval Architecture and Ocean Engineering (12):596-604. https://doi.org/10.1016/j.ijnaoe.2020.07.004
Niu W, Sui H, Niu Y, Cai K, Gao W (2016) Ship pipe routing design using NSGA-II and coevolutionary algorithm. Mathematical Problems in Engineering 1-21. https://doi.org/10.1155/2016/7912863
Park J, Storch R (2002) Pipe-routing algorithm development:case study of a ship engine room design. Expert Systems with Applications, 23(3):299-309. https://doi.org/10.1016/s0957-4174(02)00049-0
Qu Y, Jiang D, Gao G, Huo Y (2016) Pipe routing approach for aircraft engines based on ant colony optimization. Journal of Aerospace Engineering 29(3):04015057. https://doi.org/10.1061/(asce) as.1943-5525.0000543
Ren T, Zhu Z, Dimirovski G, Gao Z, Sun X, Yu H (2013) A new pipe routing method for aero-engines based on genetic algorithm. Proceedings of the Institution of Mechanical Engineers, Part G:Journal of Aerospace Engineering 228(3):424-434. https://doi.org/10.1177/0954410012474134
Sandurkar S, Chen W (1999) GAPRUS-genetic algorithms based pipe routing using tessellated objects. Computers In Industry 38(3):209-223. https://doi.org/10.1016/s0166-3615(98)00130-4
Sui H, Niu W (2016) Branch-pipe-routing approach for ships using improved genetic algorithm. Frontiers of Mechanical Engineering 11(3):316-323. https://doi.org/10.1007/s11465-016-0384-z
Wang H, Zhao C, Yan W, Feng X (2006) Three-dimensional multi-pipe route optimization based on genetic algorithms. IFIP International Federation for Information Processing, 177-183. https://doi.org/10.1007/0-387-34403-9_23
Wang Y, Yu Y, Li K, Zhao X, Guan G (2018) A human-computer cooperation improved ant colony optimization for ship pipe route design. Ocean Engineering 150:12-20. https://doi.org/10.1016/j.oceaneng.2017.12.024
Wu L, Tian X, Wang H, Liu Q, Xiao W (2019) Improved ant colony optimization algorithm and its application to solve pipe routing design. Assembly Automation 39(1):45-57. https://doi.org/10.1108/aa-02-2018-022
Wünsche B (1998) A Survey and Evaluation of Mesh Reduction Techniques
Zhou J, Liang G, Deng T, Gong J (2017) Route optimization of pipeline in gas-liquid two-phase flow based on genetic algorithm. International Journal of Chemical Engineering 2017:1-9. https://doi.org/10.1155/2017/1640303

Memo

Memo:
Received date: 2020-06-03;Accepted date:2022-06-02。
Foundation item:This study is supported the Directorate of Research and Community Engagement, Universitas Indonesia, and scheme of Research Collaboration, contract number:NKB-1954/UN2. R3.1/HKP.05.00/2019.
Corresponding author:null null,E-mail:gunawan_kapal@eng.ui.ac.id
Last Update: 2022-08-17