Skip to main content

Optimization Algorithm for Balancing and Sequencing Mixed Assembly Line

  • Conference paper
Pervasive Computing and the Networked World (ICPCA/SWS 2013)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 8351))

  • 3119 Accesses

Abstract

Mixed model assembly line is increasingly applied in the complex mechanical and electronic products assembly line. But due to the number of parts involved and the variety of the assembled product, each workstation in the mixed model assembly line has different assembly time in different stages, which increase the difficulty of optimization in mixed model assembly line. This paper starts with two levels, namely “balancing” and “sequencing”. Based on “balancing model method” and “sequencing model method”, this paper establishes a multi-objective optimization model in mixed model assembly line and put forward an integrated scheduling algorithm combining balance with optimization. Finally, a case study to manifest the validity and reliability of the method is presented.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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. Rabbani, M., Kazemi, S.M.: Mixed model U-line balancing type-1 problem: A new approach. Journal of Manufacturing Systems 31(2), 131–138 (2012)

    Article  Google Scholar 

  2. Mamun, A.A., Khaled, A.A., Ali, S.M., Chowdhury, M.M.: A heuristic approach for balancing mixed-model assembly line of type i using genetic algorithm. International Journal of Production Research 50(18), 5106–5116 (2012)

    Article  Google Scholar 

  3. Li, J., Gao, J., Sun, L.: Sequencing minimum product sets on mixed-model U-lines to minimise work overload. International Journal of Production Research 50(18), 4977–4993 (2012)

    Article  Google Scholar 

  4. Lin, D.-Y., Chu, Y.-M.: The mixed-product assembly line sequencing problem of a door-lock company in Taiwan. Computers and Industrial Engineering (2012)

    Google Scholar 

  5. Oliveira, F.S., Vittori, K., Russel, R.M.O., Travassos, X.L.: Mixed assembly line rebalancing: A binary integer approach applied to real world problems in the automotive industry. International Journal of Automotive Technology 13(6), 933–940 (2012)

    Article  Google Scholar 

  6. Moradi, H., Zandieh, M.: An imperialist competitive algorithm for a mixed-model assembly line sequencing problem. Journal of Manufacturing Systems 32(1), 46–54 (2013)

    Article  Google Scholar 

  7. Fu, J., Zhao, C., Xu, Q., Ho, T.C.: Debottleneck of multistage material-handling processes via simultaneous hoist scheduling and production line retrofit. Industrial and Engineering Chemistry Research 52(1), 123–133 (2013)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Yabo, L., Yang, W., Feng, Z. (2014). Optimization Algorithm for Balancing and Sequencing Mixed Assembly Line. In: Zu, Q., Vargas-Vera, M., Hu, B. (eds) Pervasive Computing and the Networked World. ICPCA/SWS 2013. Lecture Notes in Computer Science, vol 8351. Springer, Cham. https://doi.org/10.1007/978-3-319-09265-2_43

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-09265-2_43

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09264-5

  • Online ISBN: 978-3-319-09265-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics