Acta Informatica Pragensia 2021, 10(1), 108-120 | DOI: 10.18267/j.aip.1494197

Effective Designing of Order Picking Systems Using Dynamic Simulation

Petra Kašparová ORCID..., Jakub Dyntar
Faculty of Economics, Technical University of Liberec, Voroněžská 13, 46001 Liberec, Czech Republic

In this article, we describe the use of dynamic simulation when designing an effective system for order picking within a distribution warehouse. The simulation model was created in the Witness software environment for discrete dynamic simulation and is a modification of a general simulation model of material flows in supplier systems. Using the example of a batch system for picking orders in a drugstore goods warehouse, we discuss the possibilities of using a general simulation model of material flows as an effective framework for the development of system support for warehouse processes using WMS. The simulation model is based on the possibility of dividing any material flow in the supply system into a finite number of movements with the possibility of using one of the sources and fulfilment of certain conditions. In order to achieve the required optimisation of the order picking system, which depends, in particular, on the unknown duration of goods collection at the picking location, and on the duration of goods sorting in consolidation, the “what-if” analysis has been used as a tool to measure the impact of uncertainty of one or more variables entering the model on the uncertainty of output variables. The study showed that minimisation of the number of physical elements in the model leads to a significantly higher speed of its operation. By means of dynamic simulation, it is possible to test a large number of variants of the picking system layout in a relatively short time and minimise the risk of erroneous decisions associated with the implementation of a suitable WMS.

Keywords: Picking of orders, Controlled warehouse, Warehouse management system, Dynamic simulation, Logistics.

Received: March 7, 2021; Revised: May 13, 2021; Accepted: May 14, 2021; Prepublished online: May 17, 2021; Published: June 30, 2021  Show citation

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Kašparová, P., & Dyntar, J. (2021). Effective Designing of Order Picking Systems Using Dynamic Simulation. Acta Informatica Pragensia10(1), 108-120. doi: 10.18267/j.aip.149
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References

  1. Altarazi, S. A., & Ammouri, M. M. (2018). Concurrent manual-order-picking warehouse design: A simulation-based design of experiments approach. International Journal of Production Research, 56(23), 7103-7121. https://doi.org/10.1080/00207543.2017.1421780 Go to original source...
  2. Baio, G., & Dawid, A. P. (2015). Probabilistic sensitivity analysis in health economics. Statistical Methods in Medical Research, 24(6), 615-634. https://doi.org/10.1177/0962280211419832 Go to original source...
  3. Bolaños Zuñiga, J., Saucedo Martínez, J. A., Salais Fierro, T. E., & Marmolejo Saucedo, J. A. (2020). Optimization of the Storage Location Assignment and the Picker-Routing Problem by Using Mathematical Programming. Applied Sciences, 10(2), no. 534. https://doi.org/10.3390/app10020534 Go to original source...
  4. Bottani, E., Volpi, A., & Montanari, R. (2019). Design and optimization of order picking systems: An integrated procedure and two case studies. Computers & Industrial Engineering, 137, no. 106035. https://doi.org/10.1016/j.cie.2019.106035 Go to original source...
  5. Cano, J. A., Correa-Espinal, A. A., & Gómez-Montoya, R. A. (2017). An Evaluation of Picking Routing Policies to Improve Warehouse Efficiency. International Journal of Industrial Engineering and Management, 8(4), 229-238. Go to original source...
  6. Cano, J. A., Correa-Espinal, A. A., & Gómez-Montoya, R. A. (2020). Mathematical programming modeling for joint order batching, sequencing and picker routing problems in manual order picking systems. Journal of King Saud University - Engineering Sciences, 32(3), 219-228. https://doi.org/10.1016/j.jksues.2019.02.004 Go to original source...
  7. Çelk, M., & Süral, H. (2014). Order picking under random and turnover-based storage policies in fishbone aisle warehouses. IIE Transactions, 46(3), 283-300. https://doi.org/10.1080/0740817X.2013.768871 Go to original source...
  8. Dallari, F., Marchet, G., & Melacini, M. (2009). Design of order picking system. The International Journal of Advanced Manufacturing Technology, 42(1-2), 1-12. https://doi.org/10.1007/s00170-008-1571-9 Go to original source...
  9. de Koster, R., Le-Duc, T., & Roodbergen, K. J. (2007). Design and control of warehouse order picking: A literature review. European Journal of Operational Research, 182(2), 481-501. https://doi.org/10.1016/j.ejor.2006.07.009 Go to original source...
  10. Dyntar, J. (2018). Návrh a optimalizace dodavatelských systémů s využitím dynamické simulace. FinEco.
  11. Faber, N., De Koster, R., & Van De Velde, S. (2002). Linking warehouse complexity to warehouse planning and control structure: An exploratory study of the use of warehouse management information systems. International Journal of Physical Distribution & Logistics Management, 32, 381-395. https://doi.org/10.1108/09600030210434161 Go to original source...
  12. Fukunari, M., & Malmborg, C. J. (2008). A heuristic travel time model for random storage systems using closest open location load dispatching. International Journal of Production Research, 46(8), 2215-2228. https://doi.org/10.1080/00207540601118462 Go to original source...
  13. Gros, I., & Dyntar, J. (2015). Matematické modely pro manažerské rozhodování. Vysoká škola chemicko-technologická v Praze.
  14. Gu, J., Goetschalckx, M., & McGinnis, L. F. (2007). Research on warehouse operation: A comprehensive review. European Journal of Operational Research, 177(1), 1-21. https://doi.org/10.1016/j.ejor.2006.02.025 Go to original source...
  15. Gue, K. R., & Meller, R. D. (2009). Aisle configurations for unit-load warehouses. IIE Transactions, 41(3), 171-182. https://doi.org/10.1080/07408170802112726 Go to original source...
  16. Helo, P. (2000). Dynamic modelling of surge effect and capacity limitation in supply chains. International Journal of Production Research, 38, 4521-4533. https://doi.org/10.1080/00207540050205271 Go to original source...
  17. Ho, Y.-C., & Lin, J.-W. (2017). Improving order-picking performance by converting a sequential zone-picking line into a zone-picking network. Computers & Industrial Engineering, 113, 241-255. https://doi.org/10.1016/j.cie.2017.09.014 Go to original source...
  18. Lahmar, M. (2007). Facility Logistics: Approaches and Solutions to Next Generation Challenges. CRC Press. Go to original source...
  19. Law, A. M. (2013). Simulation modeling and analysis. Fifth edition. McGraw-Hill Education.
  20. Li, K., Li, W., Chen, Z., & Liu, Y. (2018). Computational Intelligence and Intelligent Systems: 9th International Symposium, ISICA 2017, Revised Selected Papers, Part II. Springer. https://doi.org/10.1007/978-981-13-1651-7 Go to original source...
  21. Manzini, R., Ferrari, E., Gamberi, M., Persona, A., & Regattieri, A. (2005). Simulation performance in the optimisation of the supply chain. Journal of Manufacturing Technology Management, 16, 127-144. https://doi.org/10.1108/17410380510576796 Go to original source...
  22. Manzini, R., Gamberi, M., Persona, A., & Regattieri, A. (2007). Design of a class based storage picker to product order picking system. The International Journal of Advanced Manufacturing Technology, 32(7), 811-821. https://doi.org/10.1007/s00170-005-0377-2 Go to original source...
  23. Önüt, S., Tuzkaya, U. R., & Doğaç, B. (2008). A particle swarm optimization algorithm for the multiple-level warehouse layout design problem. Computers & Industrial Engineering, 54(4), 783-799. https://doi.org/10.1016/j.cie.2007.10.012 Go to original source...
  24. Pan, J. C.-H., Wu, M.-H., & Chang, W.-L. (2014). A travel time estimation model for a high-level picker-to-part system with class-based storage policies. European Journal of Operational Research, 237(3), 1054-1066. https://doi.org/10.1016/j.ejor.2014.02.037 Go to original source...
  25. Parikh, P. J., & Meller, R. D. (2008). Selecting between batch and zone order picking strategies in a distribution center. Transportation Research Part E: Logistics and Transportation Review, 44(5), 696-719. https://doi.org/10.1016/j.tre.2007.03.002 Go to original source...
  26. Petersen, C. G., & Aase, G. (2004). A comparison of picking, storage, and routing policies in manual order picking. International Journal of Production Economics, 92(1), 11-19. https://doi.org/10.1016/j.ijpe.2003.09.006 Go to original source...
  27. Pichery, C. (2014). Sensitivity Analysis. In P. Wexler (Ed.), Encyclopedia of Toxicology (pp. 236-237). Academic Press. https://doi.org/10.1016/B978-0-12-386454-3.00431-0 Go to original source...
  28. Riddalls, C. E., Bennett, S., & Tipi, N. S. (2000). Modelling the dynamics of supply chains. International Journal of Systems Science, 31(8), 969-976. https://doi.org/10.1080/002077200412122 Go to original source...
  29. Shah, J. (2009). Supply Chain Management: Text and Cases. Pearson Education India.
  30. Scholz, A., Henn, S., Stuhlmann, M., & Wäscher, G. (2016). A new mathematical programming formulation for the Single-Picker Routing Problem. European Journal of Operational Research, 253(1), 68-84. https://doi.org/10.1016/j.ejor.2016.02.018 Go to original source...
  31. Sooksaksun, N. (2012). Pareto-Based Multi-Objective Optimization for Two-Block Class-Based Storage Warehouse Design. Industrial Engineering and Management Systems, 11(4), 331-338. https://doi.org/10.7232/iems.2012.11.4.331 Go to original source...
  32. Tompkins, J. A., White, J. A., Bozer, Y. A., & Tanchoco, J. M. A. (2010). Facilities Planning. John Wiley & Sons.
  33. Wang, Q.-Z., Chen, J.-M., Tseng, M.-L., Luan, H.-M., & Ali, M. H. (2020). Modelling green multimodal transport route performance with witness simulation software. Journal of Cleaner Production, 248, 119245. https://doi.org/10.1016/j.jclepro.2019.119245 Go to original source...
  34. Yu, M., & de Koster, R. B. M. (2009). The impact of order batching and picking area zoning on order picking system performance. European Journal of Operational Research, 198(2), 480-490. https://doi.org/10.1016/j.ejor.2008.09.011 Go to original source...
  35. Yu, Y., De Koster, R., & Guo, X. (2015). Class-Based Storage with a Finite Number of Items: Using More Classes is not Always Better. Production and Operations Management, 24, 1235-1247. https://doi.org/10.1111/poms.12334 Go to original source...

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