Advanced search
1 file | 687.12 KB Add to list

Using simulation to analyze picker blocking in manual order picking systems

Author
Organization
Abstract
The rise of the e-commerce practice makes the warehouses be confronted with ever smaller orders that must be met ever faster, often within a 24-h period. This pressures the order picking process as the orders pickers' workload becomes higher and higher, leading subsequently to congestion in the warehouse and impacting its productivity. It is therefore crucial to determine which order batching and picking policies enhance the performance of order picking activities. This paper carries out an intensive simulation study to examine the performance of different order picking policies with batching in a wide-aisle warehouse with a low-level picker-to-parts system. The performance of the system is measured in terms of total travelled distance, number of collisions between operators (congestion) and order lead times. A full factorial design is set up and the simulation output is statistically analyzed. The results are reported and thoroughly discussed.
Keywords
Order picking, Batching, Congestion, Simulation, WAREHOUSES, AISLES, SPACE

Downloads

  • 1-s2.0-S2351978917305255-main.pdf
    • full text
    • |
    • open access
    • |
    • PDF
    • |
    • 687.12 KB

Citation

Please use this url to cite or link to this publication:

MLA
Bahrami, Behnam, et al. “Using Simulation to Analyze Picker Blocking in Manual Order Picking Systems.” 27th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM-2017, edited by M Pellicciari and M Peruzzini, vol. 11, Elsevier Science, 2017, pp. 1798–808, doi:10.1016/j.promfg.2017.07.317.
APA
Bahrami, B., Aghezzaf, E.-H., & Limère, V. (2017). Using simulation to analyze picker blocking in manual order picking systems. In M. Pellicciari & M. Peruzzini (Eds.), 27th International conference on flexible automation and intelligent manufacturing, FAIM-2017 (Vol. 11, pp. 1798–1808). https://doi.org/10.1016/j.promfg.2017.07.317
Chicago author-date
Bahrami, Behnam, El-Houssaine Aghezzaf, and Veronique Limère. 2017. “Using Simulation to Analyze Picker Blocking in Manual Order Picking Systems.” In 27th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM-2017, edited by M Pellicciari and M Peruzzini, 11:1798–1808. Amsterdam, The Netherlands: Elsevier Science. https://doi.org/10.1016/j.promfg.2017.07.317.
Chicago author-date (all authors)
Bahrami, Behnam, El-Houssaine Aghezzaf, and Veronique Limère. 2017. “Using Simulation to Analyze Picker Blocking in Manual Order Picking Systems.” In 27th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM-2017, ed by. M Pellicciari and M Peruzzini, 11:1798–1808. Amsterdam, The Netherlands: Elsevier Science. doi:10.1016/j.promfg.2017.07.317.
Vancouver
1.
Bahrami B, Aghezzaf E-H, Limère V. Using simulation to analyze picker blocking in manual order picking systems. In: Pellicciari M, Peruzzini M, editors. 27th International conference on flexible automation and intelligent manufacturing, FAIM-2017. Amsterdam, The Netherlands: Elsevier Science; 2017. p. 1798–808.
IEEE
[1]
B. Bahrami, E.-H. Aghezzaf, and V. Limère, “Using simulation to analyze picker blocking in manual order picking systems,” in 27th International conference on flexible automation and intelligent manufacturing, FAIM-2017, Modena, Italy, 2017, vol. 11, pp. 1798–1808.
@inproceedings{8532693,
  abstract     = {{The rise of the e-commerce practice makes the warehouses be confronted with ever smaller orders that must be met ever faster, often within a 24-h period. This pressures the order picking process as the orders pickers' workload becomes higher and higher, leading subsequently to congestion in the warehouse and impacting its productivity. It is therefore crucial to determine which order batching and picking policies enhance the performance of order picking activities. This paper carries out an intensive simulation study to examine the performance of different order picking policies with batching in a wide-aisle warehouse with a low-level picker-to-parts system. The performance of the system is measured in terms of total travelled distance, number of collisions between operators (congestion) and order lead times. A full factorial design is set up and the simulation output is statistically analyzed. The results are reported and thoroughly discussed.}},
  author       = {{Bahrami, Behnam and Aghezzaf, El-Houssaine and Limère, Veronique}},
  booktitle    = {{27th International conference on flexible automation and intelligent manufacturing, FAIM-2017}},
  editor       = {{Pellicciari, M and Peruzzini, M}},
  issn         = {{2351-9789}},
  keywords     = {{Order picking,Batching,Congestion,Simulation,WAREHOUSES,AISLES,SPACE}},
  language     = {{eng}},
  location     = {{Modena, Italy}},
  pages        = {{1798--1808}},
  publisher    = {{Elsevier Science}},
  title        = {{Using simulation to analyze picker blocking in manual order picking systems}},
  url          = {{http://dx.doi.org/10.1016/j.promfg.2017.07.317}},
  volume       = {{11}},
  year         = {{2017}},
}

Altmetric
View in Altmetric
Web of Science
Times cited: