Skip to main content
SpringerLink
Log in

Application of Particle Swarm Optimization to Maximize Efficiency of Straight and U-Shaped Robotic Assembly Lines

  • Conference paper
  • First Online:
Book cover Distributed Computing and Artificial Intelligence, 13th International Conference

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 474))

Abstract

This paper focuses on implementing particle swarm optimization (PSO) to optimize the robotic assembly line balancing (RALB) problems with an objective of maximizing line efficiency. By maximizing the line efficiency, industries tend to utilize their resources in an efficient manner. In this paper, two layout configurations of robotic assembly lines are proposed. In this robotic assembly line balancing problem, the tasks are assigned to the workstations and the efficient robots to perform the assigned tasks are chosen based on the objective of maximizing line efficiency. Performance of the proposed PSO algorithm is evaluated on benchmark problems and compared with the best known results reported in the literature. Computational time of the proposed algorithm is better than the one reported in the literature. Comparative studies on the performance of the two layouts are also done and the results are reported.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Scholl, A., Becker, C.: State-of-the-art exact and heuristic solution procedures for simple assembly line balancing. European Journal of Operational Research 168, 666–693 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  2. Sivasankaran, P., Shahabudeen, P.: Literature review of assembly line balancing problems. The International Journal of Advanced Manufacturing Technology 73, 1665–1694 (2014)

    Article  Google Scholar 

  3. Levitin, G., Rubinovitz, J., Shnits, B.: A genetic algorithm for robotic assembly line balancing. European Journal of Operational Research 168, 811–825 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  4. Gao, J., Sun, L., Wang, L., Gen, M.: An efficient approach for type II robotic assembly line balancing problems. Computers & Industrial Engineering 56, 1065–1080 (2009)

    Article  Google Scholar 

  5. Nilakantan, J.M., Huang, G.Q., Ponnambalam, S.: An investigation on minimizing cycle time and total energy consumption in robotic assembly line systems. Journal of Cleaner Production 90, 311–325 (2015)

    Article  Google Scholar 

  6. Yoosefelahi, A., Aminnayeri, M., Mosadegh, H., Ardakani, H.D.: Type II robotic assembly line balancing problem: An evolution strategies algorithm for a multi-objective model. Journal of Manufacturing Systems 31, 139–151 (2012)

    Article  Google Scholar 

  7. Relich, M., Muszyński, W.: The use of intelligent systems for planning and scheduling of product development projects. Procedia Computer Science 35, 1586–1595 (2014)

    Article  Google Scholar 

  8. Sitek, P.: A hybrid CP/MP approach to supply chain modelling, optimization and analysis. In: 2014 Federated Conference on Proceedings of Computer Science and Information Systems (FedCSIS), pp. 1345–1352. IEEE (2014)

    Google Scholar 

  9. Nilakantan, J.M., Ponnambalam, S.: Optimizing the Efficiency of Straight and U-Shaped Robotic Assembly Lines. Swarm, Evolutionary, and Memetic Computing, pp. 582–595. Springer (2014)

    Google Scholar 

  10. Dou, J., Li, J., Lv, Q.: A hybrid particle swarm algorithm for assembly line balancing problem of type 1. In: 2011 International Conference on Proceedings of Mechatronics and Automation (ICMA), pp. 1664–1669. IEEE (2011)

    Google Scholar 

  11. Kennedy, J., Eberhart, R.: Particle swarm optimization. In: Proceedings of IEEE International Conference on Proceedings of Neural Networks, 1995, vol. 1944, pp. 1942–1948 (1995)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Mechanical and Manufacturing Engineering, Aalborg University, Aalborg, Denmark

    Mukund Nilakantan Janardhanan & Peter Nielsen

  2. School of Engineering, Monash University Malaysia, 46150, Bandar Sunway, Malaysia

    S. G. Ponnambalam

Authors
  1. Mukund Nilakantan Janardhanan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Peter Nielsen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. S. G. Ponnambalam
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mukund Nilakantan Janardhanan .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, Osaka Institute of Technology Faculty of Engineering, Osaka, Osaka, Japan

    Sigeru Omatu

  2. Faculty of Computer Science & Informatio, Universiti Teknologi Malaysia (UTM) Faculty of Computer Science & Informatio, Baharu, Malaysia

    Ali Semalat

  3. Department of Electronics and Compu, Koszalin University of Technology Department of Electronics and Compu, Koszalin, Poland

    Grzegorz Bocewicz

  4. Faculty of Electrical Engineering and Cs, Kielce University of Technology Faculty of Electrical Engineering and Cs, Kielce, Poland

    Paweł Sitek

  5. Faculty of Engineering and Science, Aalborg University Faculty of Engineering and Science, Aalborg, Denmark

    Izabela E. Nielsen

  6. ETS Ingeniería Informática, University of Sevilla ETS Ingeniería Informática, Sevilla, Spain

    Julián A. García García

  7. Departamento de Inteligencia Artificial, Universidad Politécnica de Madrid Departamento de Inteligencia Artificial, Madrid, Spain

    Javier Bajo

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Janardhanan, M.N., Nielsen, P., Ponnambalam, S.G. (2016). Application of Particle Swarm Optimization to Maximize Efficiency of Straight and U-Shaped Robotic Assembly Lines. In: Omatu, S., et al. Distributed Computing and Artificial Intelligence, 13th International Conference. Advances in Intelligent Systems and Computing, vol 474. Springer, Cham. https://doi.org/10.1007/978-3-319-40162-1_56

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-40162-1_56

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-40161-4

  • Online ISBN: 978-3-319-40162-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation