Performance assessment in order picking systems: a visual double cross-analysis
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The aim of this paper is to introduce a practice-ready systematic methodology for the management of storage assignments and allocation decisions as well as an assessment of the resulting performance in an order picking system (OPS). Built on extant and well-known metrics of performance this method implements a double cross-analysis through an original visual tool that is easy to understand by warehousing managers and practitioners. This tool is organized in two main steps. The first step is a cross-analysis that combines multiple performance indicators to help the decision-maker understand whether an OPS provides the scope for performance improvement. A comparison with potential storage configurations is then conducted in the second step through a tailored multi-scenario cross-analysis, which attempts to identify the best combination of allocation and assignment policies capable of minimizing the overall traveling performance. The proposed methodology is applied to a significant real-world OPS. The selected case study represents a reference framework for decision-makers and practitioners.
KeywordsPicking Order picking system (OPS) Storage allocation Storage assignment Case study Picker-to-part System performance
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The authors would like to heartily thank the company Fercam S.p.a. involved in this study. Especially in the name of Eng. Luca Mezzaro, for his support and his willingness to cooperate to this project.
- 1.Bartholdi JJ, Hackman ST (2017) Warehouse & distribution science. IIE Trans. http://www.warehouse-science.com/. Accessed 12 Nov 2018
- 4.Rouwenhorst B, van den Berg J, Mantel R, Zijm H (1999) UnitLoad, a decision support system for warehouse design. Int J Flex Autom Integr Manuf 7:115–127Google Scholar
- 12.Kofler M, Beham A, Wagner S, Affenzeller M (2011) Re-warehousing vs. healing: strategies for warehouse storage location assignment. In 3rd IEEE International Symposium on Logistics and Industrial Informatics (LINDI), pp 77–82. https://doi.org/10.1109/LINDI.2011.6031124
- 21.Hassini E (2008) Storage space allocation to maximize inter-replenishment times 35: 2162–2174. https://doi.org/10.1016/j.cor.2006.09.023.
- 24.Heskett J (1963) Cube-per-order index a key to warehouse stock location. Transp Distrib Manag 3:27–31Google Scholar
- 36.Smith JS, Yingde L (2012) Dynamic slotting optimization based on skus correlations in a zone-based wave-picking system. http://www.mhi.org/downloads/learning/cicmhe/colloquium/2012/yingde.pdf. Accessed 12 Nov 2018
- 38.Chiang M-h, David C-p L, Chen M-c (2013, 2011) The adaptive approach for storage assignment by mining data of warehouse management system for distribution centres. Enterp Inf Syst:37–41. https://doi.org/10.1080/17517575.2010.537784
- 42.Rao SS, Adil GK (2014) Class-Based Storage Assignment in a Unit-Load Warehouse Employing AS/RS with Inventory Space Allocation Considering Product Specific Setup to Holding Cost Ratio. Asia-Pacific J Oper Res 31:1450034. https://doi.org/10.1142/S0217595914500341 MathSciNetCrossRefzbMATHGoogle Scholar
- 55.Xie J, Yi M, Ernst AT, Li X, Song A (2014) Scaling up solutions to storage location assignment problems by genetic programming. In Simulated Evolution and Learning, pp 691–702Google Scholar
- 60.Davarzani H, Norrman A (2015) Toward a relevant agenda for warehousing research: literature review and practitioners’ input. Logist Res 8. https://doi.org/10.1007/s12159-014-0120-1
- 62.Baruffaldi G, Accorsi R, Manzini R (2018) Warehouse management system customization and information availability in 3pl companies: a decision-support tool. Ind Manag Data Syst. https://doi.org/10.1108/IMDS-01-2018-0033