Skip to main content

Advertisement

SpringerLink
Log in

Robot arc welding task sequencing using genetic algorithms

  • Published:
IIE Transactions

Abstract

This paper addresses welding task sequencing for robot arc welding process planning. Although welding task sequencing is an essential step in welding process planning, it has been considered through empirical knowledge, rather than a systematic approach. Thus, an effective task sequencing method for robot arc welding is required. Welding operations can be classified by the number of weldlines and layers. Genetic algorithms are applied to tackle those welding task sequencing problems in productivity and welding quality aspects. A genetic algorithm for the Traveling Salesman Problem (TSP) is utilized to determine welding task sequencing for a multiweldline-singlepass problem. Further, welding task sequencing for multiweldline-multipass welding is investigated and appropriate genetic algorithms are introduced. A random key genetic algorithm is presented to solve multi-robot welding task sequencing: mutliweldline with multiple robots. Finally, the genetic algorithms are implemented for the welding task sequencing of three-dimensional weld plate assemblies. Various simulation tests for a welded structure are performed to find the combination of genetic algorithm parameters suitable to weld sequencing problems and to verify the quality of genetic algorithm solutions. Robot operations for weld sequences are simulated graphically using the robot simulation software IGRIP.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Armao, F.G. (1996) Low Cost High Volume Program-Summary of Investigation Conducted to Assess the Effects of Multipass Welding on Welding Distortion and Joint Mechanical Properties. Technical report, Aluminum Company of America, Pittsburgh, PA, pp. 13–14.

    Google Scholar 

  • Coit, D.W. and Smith, A.E. (1996) Adaptive penalty methods for genetic optimization of constrained combinatorial problems. INFORM Journal on Computing, 8 (2), 173.

    Google Scholar 

  • Edan, Y. and Nof, S.Y. (1995) Motion economy analysis for robotic kitting tasks. International Journal of Production Research, 33 (5), 1213–1227.

    Google Scholar 

  • Fukuda, S. and Yoshikawa, K. (1990) Determination of welding sequence: a neural net approach. Engineering Analysis, 7 (2), 78–82.

    Google Scholar 

  • Goldberg, D.E. (1989) Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley, New York, pp. 170–171.

    Google Scholar 

  • Holland, J.H. (1975) Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor, MI, USA.

    Google Scholar 

  • Huang, M.W., Hsieh, C.C. and Arora, J.S. (1997) A genetic algorithms for sequencing type problems in engineering design. International Journal for Numerical Methods in Engineering, 40, 3105–3115.

    Google Scholar 

  • Kim, D.W. (1994) A feature-based process planning system for robotic arc welding. Ph.D. dissertation, Hokkaido University, Sapporo, Japan.

  • Kim, D.W., Choi, J.S. and Nnaji, B.O. (1998) Robot arc welding operations planning with a rotating/tilting positioner, International Journal of Production Research, 36 (4), 957–979.

    Google Scholar 

  • Koza, J.R. (1992) Genetic Programming: On the Programming of Computers by Means of Natural Selection, The MIT Press, Cambridge, MA.

    Google Scholar 

  • Latombe, J.C., Wilson, R.H. and Cazals, F. (1997) Assembly sequencing with toleranced parts. CAD, 29 (2), 159–179.

    Google Scholar 

  • Lee, Y. and Sanii, E.T. (1997) Process selection and operation sequencing based on feature extraction. Engineering Design and Automation, 2 (4), 307–320.

    Google Scholar 

  • Maimon, O. (1990) The robot task-sequencing planning problem. IEEE Transactions on Robotics and Automation, 6 (6), 760–765.

    Google Scholar 

  • Masubuchi, K. (1980) Analysis of Welded Structures: Residual Stresses, Distortion, and their Consequences, Pergamon Press Inc., New York, pp. 60–236.

    Google Scholar 

  • Michalewicz, Z. (1992) Genetic Algorithms + Data Structure = Evolution Programs, Springer-Verlag, New York, pp. 168–176.

    Google Scholar 

  • Myhr, O.R., Klokkehaug, S., Groug, Ø., Fjær, H.G. and Kluken, A.O. (1998) Modeling of microstructure evolution, residual stresses and distortions in 6082-T6 aluminum weldments. Welding Journal, 77 (7), 286–292.

    Google Scholar 

  • Norman, B.A. (1995) The random keys genetic algorithm for complex scheduling problems. Ph.D. Dissertation, University of Michigan, Ann Arbor, MI.

  • Park, J.H. and Asada, H. (1994) Sequence optimization for high speed robotic assembly using simulated annealing, in Proceedings of the IEEE International Conference on Robotics and Automation, IEEE Robotics and Automation Society, 8–13 May, San Diego, CA, USA, pp. 3441–3446.

  • Prasad, N.S. and Srinivasan, M. (1997) Effect of boundary restraints and welding sequence on residual stresses in weldments. International Journal for the Joining of Materials, 9 (1), 37–42.

    Google Scholar 

  • Radaj, D. (1992) Heat Effects of Welding, Springer-Verlag, New York, 122–260.

    Google Scholar 

  • Rubinovitz, J. and Wysk, R.A. (1988) Task level off-line programming system for robotic arc welding - an overview, Journal of Manufacturing Systems, 7(4), 293–299.

    Google Scholar 

  • Shaefer, C.G. and Smith, S.J. (1988) The ARGOT Strategy II: Combinatorial Optimizations, Technical Report, Thinking Machine Company.

  • Shin, C.K., Hong, D.S. and Cho, H.S. (1995) Disassemblability analysis for generating robotic assembly sequences, in Proceedings of the IEEE International Conference on Robotics and Automation, IEEE Robotics and Automation Society, 21–27 May, Nagoya, Japan, pp. 1284–1289.

  • Starkwether, T., McDaniel, Mathias, K., Whitley, C. and Whitley. D. (1991) A comparison of genetic sequencing operators, in Proceedings of the 4th International Conference on Genetic Algorithms, Los Altos, CA, Morgan Kaufmann Publishers, pp. 70–72.

    Google Scholar 

  • Swaminathan, A. and Barber, K.S. (1995) APE: an experience-based assembly sequence planner for mechanical assembly, in Proceedings of the IEEE International Conference on Robotics and Automation, IEEE Robotics and Automation Society, 21–27 May, Nagoya, Japan, pp. 1278–1238.

  • Wittenberg, G. (1995) Developments in Off-line programming: an overview. Industrial Robot, 22 (3), 21–104.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Industrial Engineering, University of Pittsburgh, 1048 Benedum Hall, Pittsburgh, PA, 15261, USA

    Kyoung-Yun Kim, Dong-Won Kim & Bart O. Nnaji

Authors
  1. Kyoung-Yun Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dong-Won Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bart O. Nnaji
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kim, KY., Kim, DW. & Nnaji, B.O. Robot arc welding task sequencing using genetic algorithms. IIE Transactions 34, 865–880 (2002). https://doi.org/10.1023/A:1015732825817

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1015732825817

Keywords

Search

Navigation