Cluster Computing

, Volume 22, Supplement 3, pp 5505–5519 | Cite as

Research on visual 3D assembly process design and simulation for marine diesel engine

  • Zhang HuiEmail author
  • Fei Tianming
  • Guan Wei
  • Zhang Shengwen
  • Jin Zhipeng
  • Tang Weikang


In view of the backward traditional assembly process design model in shipbuilding industry, the research on the visual assembly process design and simulation of the marine diesel engine is an innovation for the marine diesel engine manufacturing model. This paper studied the key technologies such as structural assembly process design and assembly process simulation. In addition, following the principle of unified data source, through independent development and application on the platforms of Teamcenter and Vis MockUp, this research removed the obstacles in the integration of visual 3D assembly process design and simulation, took the lead in transforming the whole marine diesel engine assembly model from 2 dimensions to 3 dimensions, and made the methods of process verification and assessment more advanced. Finally, taking key parts of certain marine diesel engine as an example, this research verified the feasibility of the assembly process design system, and improved the stability and reliability of the marine diesel engine assembly process design.


Marine diesel engine Visualization Assembly process design Process simulation Process resource 


  1. 1.
    Cai, C., Weng, X., Zhang, C.: A novel approach for marine diesel engine fault diagnosis. Clust. Comput. 20(2), 1691–1702 (2017)CrossRefGoogle Scholar
  2. 2.
    Hui, Z., Jian, Z., Shengwen, Z., Pan, Z.: Marine diesel engine box parts CAD/CAPP/CAM integrate system with machining feature self defined. Comput. Integr. Mak. Syst. 09, 2086–2092 (2014)Google Scholar
  3. 3.
    Petrukhin, A.V., Saninskii, V.A., Moskvicheva, N.P., Kochkin, M.V.: Automated selection of components in bearing assembly for marine diesel engines. Russ. Eng. Res. 35(7), 500–504 (2015)CrossRefGoogle Scholar
  4. 4.
    Liu, L.: The Key Technology of Visualization of Assembly Process Planning Research of Wuhan. Wuhan University of Technology Industrial Engineering, Wuhan (2012)Google Scholar
  5. 5.
    Ghandi, S., Masehian, E.: Review and taxonomies of assembly and disassembly path planning problems and approaches. Comput. Aided Des. 67–68, 68–86 (2015)Google Scholar
  6. 6.
    Burggraf, P., Wagner, J., Luck, K., Adlon, T.: Cost-benefit analysis for disruption prevention in low-volume assembly. Prod. Eng. 11(3), 331–342 (2017)CrossRefGoogle Scholar
  7. 7.
    Bikas, C., Argyrou, A., Pintzos, G., Giannoulis, C., Sipsas, K., Papakostas, N., Chryssolouris, G.: An automated assembly process planning system. Procedia CRIP 44, 222–227 (2016)CrossRefGoogle Scholar
  8. 8.
    Guo, Q., Tang, H., Guo, S., Li, Y., Zhang, J.: An automatic assembly CAD system of plastic profile calibrating die based on feature recognition. Int. J. Adv. Manuf. Technol. 85(9–12), 2577–2587 (2016)CrossRefGoogle Scholar
  9. 9.
    Wang, H., Rong, Y., Xiang, D.: Mechanical assembly planning using ant colony optimization. Comput. Aided Des. 47, 59–71 (2014)CrossRefGoogle Scholar
  10. 10.
    Winkes, P.A., Aurich, J.C.: Method for an enhanced assembly planning process with systematic virtual reality inclusion. Procedia CIRP 37, 152–157 (2015)CrossRefGoogle Scholar
  11. 11.
    Hold, P., Ranz, F., Sihn, W., Hummel, W.: Planning operator support in cyber-physical assembly systems. IFAC-PapersOnLine 49(32), 60–65 (2016)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Muller, R., Vette, M., Horauf, L., Speicher, C.: Consistent data usage and exchange between virtuality and reality to manage complexities in assembly planning. Procedia CIRP 44, 73–78 (2016)CrossRefGoogle Scholar
  13. 13.
    Kardos, C., Kovacs, A., Vancza, J.: Towards feature-based human-robot assembly process planning. Procedia CIRP 57, 516–521 (2016)CrossRefGoogle Scholar
  14. 14.
    Liu, M., Ma, J., Lin, L., Ge, M., Wang, Q., Liu, C.: Intelligent assembly system for mechanical products and key technology based on internet of things. J. Intell. Manuf. 28(2), 271–299 (2017)CrossRefGoogle Scholar
  15. 15.
    Li, X., Qin, K., Zeng, B., Gao, L., Wang, L.: A dynamic parameter controlled harmony search algorithm for assembly sequence planning. Int. J. Adv. Manuf. Technol. pp. 1–13 (2017)Google Scholar
  16. 16.
    Li, X., Qin, K., Zeng, B., Gao, L., Jiezhi, S.: Assembly sequence planning based on an improved harmony search algorithm. Int. J. Adv. Manuf. Technol. 84(9–12), 2367–2380 (2016)CrossRefGoogle Scholar
  17. 17.
    Xin, L., Jianzhong, S., Yujun, C.: An efficient method of automatic assembly sequence planning for aerospace industry based on genetic algorithm. Int. J. Adv. Manuf. Technol. 90(5–8), 1307–1315 (2017)CrossRefGoogle Scholar
  18. 18.
    Wan, W., Harada, K.: Integrated assembly and motion planning using regrasp graphs. Robot Biomim, 3, 18 (2016)CrossRefGoogle Scholar
  19. 19.
    Wang, Y., Tian, D.: A weighted assembly precedence graph of assembly sequence planning. Int. J. Adv. Manuf. Technol. 83(1–4), 99–115 (2016)CrossRefGoogle Scholar
  20. 20.
    Xu, Z.J., Wang, P., Wang, Q.H., Li, J.R.: Integrated part modeling and assembly modeling from the perspective of process. J. Intell. Manuf. pp 1–24 (2016)Google Scholar
  21. 21.
    Zhang, H., Liu, H., Li, L.: Research on a kind of assembly sequence planning based on immune algorithm and particle swarm optimization algorithm. Int. J. Adv. Manuf. Technol. 71(5–8), 795–808 (2014)CrossRefGoogle Scholar
  22. 22.
    Yao, Y.X., Xia, P.J., Liu, J.S., Li, J.G.: A pragmatic system to support interactive assembly planning and training in an immersive virtual environment (I-VAPTS). Int. J. Adv. Manuf. Technol. 30, 959–967 (2006)CrossRefGoogle Scholar
  23. 23.
    Yang, Q., Wu, D.L., Zhu, H.M., Bao, J.S., Wei, Z.H.: Assembly operation process planning by mapping a virtual assembly simulation to real operation. Comput. Ind. 64, 869–879 (2013)CrossRefGoogle Scholar
  24. 24.
    Yoon, C.J.: Assembly simulations in virtual environments with optimized haptic path and sequence. Robot. Comput. Integr. Manuf. 27(2), 306–317 (2011)CrossRefGoogle Scholar
  25. 25.
    Yang, R.D., Fan, X.M., Wu, D.L., Yan, J.Q.: A virtual reality-based experiment environment for ,engine assembly line workplace planning and ergonomics evaluation. In: Virtual Reality—Second International Conference, pp. 594–603 (2007)Google Scholar
  26. 26.
    Xitian, T., Junhao, G., Jianjun, T., et al.: Airplane 3D digital assembly process design and management technology. Aeronaut. Manuf. Technol. 473(4), 51–54 (2015)Google Scholar
  27. 27.
    Hongjun, Q.: Knowledge-based Study on Key Technology of Aircraft Assembly Process Design. Northwestern Polytechnical University, Xian (2006)Google Scholar
  28. 28.
    Tingting, F.: MBD-based Aircraft Assembly Process Planning and Simulation. Nanjing University of Aeronautics and Astronautics, Nanjing (2011)Google Scholar
  29. 29.
    Yuan, M., Jie, L., Bohu, L.: Meta-model based study of complex system modelling method. BOM-based study of assembly process system. J. Syst. Simul. 04(45), 411–414 (2002)Google Scholar
  30. 30.
    Milberg, J., Wisbacher, J.: Acoustic test procedures—a powerful method for quality assurance and process monitoring in assembly. CIRP Ann. Manuf. Technol. 41(1), 25–28 (1992)CrossRefGoogle Scholar
  31. 31.
    Holmstedt, P., Mårtensson, L., Arnström, A.: Cooperation of man and robot assembly—an evaluation of an industrial flexible assembly system. CIRP Ann. Manuf. Technol. 46(1), 11–14 (1997)CrossRefGoogle Scholar
  32. 32.
    Yingjie, X., Hongjun, D., Xiaobing, L., et al.: Study of BOM management technology in CAPP. Mach. Des. Manuf. 33(1), 87–89 (2004)Google Scholar
  33. 33.
    Yusof, Y., Latif, K.: Survey on computer-aided process planning. Int. J. Adv. Manuf. Technol. 75, 77–89 (2014)CrossRefGoogle Scholar
  34. 34.
    Hairu, Y.: DELMIA-based Study and Application of Navigation Product Assembly Process Simulation Technology. Hebei University of Science and Technology, Hebei (2016)Google Scholar
  35. 35.
    Yaoqi, Y.: Visual Technology Based Study and Implementation of Computer-assisted Assembly Process Design System. Beijing University of Posts and Telecommunications, Beijing (2006)Google Scholar
  36. 36.
    Meian, L.: Study of Airframe Assembly Process and Simulation Technology. Nanjing University of Aeronautics and Astronautics, Nanjing (2010)Google Scholar
  37. 37.
    Wang, X., Ong, S.K., Nee, A.Y.C.: A comprehensive survey of augmented reality assembly research. Adv. Manuf. 4(1), 1–22 (2016)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  • Zhang Hui
    • 1
    • 2
    Email author
  • Fei Tianming
    • 1
    • 2
  • Guan Wei
    • 3
  • Zhang Shengwen
    • 1
    • 2
  • Jin Zhipeng
    • 1
    • 2
  • Tang Weikang
    • 1
    • 2
  1. 1.School of Mechanical EngineeringJiangsu University of Science and TechnologyZhenjiangChina
  2. 2.Jiangsu Provincial Key Laboratory of Advanced Manufacture and Process for Marine Mechanical EquipmentJiangsu University of Science and TechnologyZhenjiangChina
  3. 3.Advanced Manufacturing Tech. Design DeptHudong Heavy Machinery Co. LtdShanghaiChina

Personalised recommendations