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Ship block assembly sequence planning considering productivity and welding deformation

  • Kang, Minseok (Graduate School of Ocean Systems Engineering, Dept. of Mechanical Engineering, KAIST) ;
  • Seo, Jeongyeon (Graduate School of Ocean Systems Engineering, Dept. of Mechanical Engineering, KAIST) ;
  • Chung, Hyun (Department of Naval Architecture & Ocean Engineering, Chungnam National University)
  • Received : 2017.02.09
  • Accepted : 2017.09.13
  • Published : 2018.07.31

Abstract

The determination of assembly sequence in general mechanical assemblies plays an important role in terms of manufacturing cost, duration and quality. In the production of ships and offshore plants, the consideration of productivity factors and welding deformation is crucial in determining the optimal assembly sequence. In shipbuilding and offshore industries, most assembly sequence planning has been done according to engineers' decisions based on extensive experience. This may result in error-prone planning and sub-optimal sequence, especially when dealing with unfamiliar block assemblies composed of dozens of parts. This paper presents an assembly sequence planning method for block assemblies. The proposed method basically considers geometric characteristics of blocks to determine feasible assembly sequences, as well as assembly process and productivity factors. Then the assembly sequence with minimal welding deformation is selected based on simplified welding distortion analysis. The method is validated using an asymmetric assembly model and the results indicate that it is capable of generating an optimal assembly sequence.

Keywords

References

  1. Bourjault, A., 1984. Contributionune approche methodologique del'assemblage automatise: elaboration automatique dessequences operatiores. Thesis d'Etat. Universite de Franche-Comte, Besancon (in French).
  2. Chen, W.C., Tai, P.H., Deng, W.J., Heieh, L.F., 2008. A three-stage integrated approach for assembly sequence planning using neural networks. Expert Syst. Appl. 32 (1), 245-253.
  3. Cheng, R., Gen, M., Tsujimura, Y., 1996. A tutorial survey of job-shop scheduling problems using genetic algorithms-I. Represent. Comput. Ind. Engng 30 (4), 983-997. https://doi.org/10.1016/0360-8352(96)00047-2
  4. Defazio, T.L., Whitney, D.E., 1987. Simplified generation of all mechanical assembly sequences. IEEE J. Robot. Autom. RA-3 (6), 640-658.
  5. Ha, Y.S., 2011. A study on weldment boundary condition for elasto-plastic thermal distortion analysis of large welded structures. J. KWJS 29-4, 48-53.
  6. Ha, Y.S., 2013. Analytical methodology obtaining an optimal welding sequence for least distortion of welded structure. JWJ 31 (3), 54-59.
  7. Hardikar, K.D., Nidgalkar, D.J., Inamdar, K.H., 2012. Techniques to ensure minimum distortion of an assembly of metal parts induced due to the process of welding used for an assembly. IJSER 3 (2), 1-4.
  8. Kim, H., Kang, J., Park, S., 2000. Scheduling of shipyard block assembly process using constraint satisfaction problem. Asia Pac. Mgmt. Rev. 7 (1), 119-138.
  9. Kim, J.W., Jang, B.S., Kang, S.W., 2014a. A study on an efficient prediction of welding deformation for T-joint laser welding of sandwich panel PART II: proposal of a method to use shell element model. Int. J. Nav. Archit. Ocean. Eng. 6, 245-256. https://doi.org/10.2478/IJNAOE-2013-0176
  10. Kim, T.J., Jang, B.S., Kang, S.W., 2014b. Welding deformation analysis based on improved equivalent strain method considering the effect of temperature gradients. Int. J. Nav. Archit. Ocean Eng. 7 (1), 157-173. https://doi.org/10.1515/ijnaoe-2015-0012
  11. Kim, M.K., Kang, M.S., Chung, H., 2015a. Simplified welding distortion analysis for fillet welding using composite shell elements. IJNAOE 7 (3), 452-465.
  12. Kim, T.J., Jang, B.S., Kang, S.W., 2015b. Welding deformation analysis based on improved equivalent strain method to cover external constraint during cooling stage. Int. J. Nav. Archit. Ocean. Eng. 7, 805-816. https://doi.org/10.1515/ijnaoe-2015-0057
  13. Mula, J., Poler, R., Garcia-Sabater, J.P., Lario, F.C., 2006. Models for production planning under uncertainty: a review. Int. J. Prod. Econ. 103, 271-285. https://doi.org/10.1016/j.ijpe.2005.09.001
  14. Park, W., Kim, K.J., Won, S.T., 2013. Deformation and residual stress analysis of automotive frame following as welding sequency variation. Trans. Korean Soc. Automot. Eng. 21 (3), 50-57. https://doi.org/10.7467/KSAE.2013.21.3.050
  15. Shipeng, Q., Zuhua, J., Ningrong, T., 2013. An integrated method for block assembly sequence planning in shipbuilding. Int. J. Adv. Manuf. Tech. 69, 1123-1135. https://doi.org/10.1007/s00170-013-5087-6
  16. Su, Q., 2014. Applying case-based reasoning in assembly sequence planning. Int. J. Prod. Res. 45, 29-47.
  17. Wang, J., 2013. Reduction of welding distortion for an improved assembly process for hatch coaming production. SNAME 737-744.
  18. Yasin, A., Puteh, N., Daud, R., 2010. Product assembly sequence optimization based on genetic algorithm. Int. J. Comput. Sce. Eng. Commun. 02 (09), 3065-3070.
  19. Zhang, Y.Z., Ni, J., Lin, Z.Q., Lai, X.M., 2002. Automated sequencing and sub-assembly detection in automobile body assembly planning. J. Mater. Process. Technol. 129 (1-3), 490-494. https://doi.org/10.1016/S0924-0136(02)00621-0

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