Abstract
Designing the operating policies of picking systems, which connect inventory and production/assembly lines in a manufacturing system, involves determining replenishment methods for individual items. These replenishment methods affect the overall labor cost and flexibility of the picking system by determining the frequency and quantity of item picking. To design the replenishment method, in this paper, we propose a data-driven decision support framework that provides guidance in comprehending features in a picking system based on demand, size, and value of individual items. The proposed framework is then applied to a real-world case for validation.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Wiendahl, H., ElMaraghy, H.A., Nyhuis, P., et al.: Changeable manufacturing- classification, design and operation. CIRP Ann.-Manuf. Technol. 56(2), 783–809 (2007)
Le-Duc, T., de Koster, R.: Travel distance estimation and storage zone optimization in a 2-block class-based storage strategy warehouse. Int. J. Prod. Res. 43, 3561–3581 (2005)
de Koster, R., Le-Duc, T., Roodbergen, K.J.: Design and control of warehouse order picking: a literature review. Eur. J. Oper. Res. 182, 481–501 (2007)
Karaesmen, F., Dallery, Y.: A performance comparison of pull type control mechanisms for multi-stage manufacturing. Int. J. Prod. Econ. 68, 59–71 (2000)
Liberopoulos, G., Dallery, Y.: A unified framework for pull control mechanisms in multi-stage manufacturing systems. Ann. Oper. Res. 93, 325–355 (2000). https://doi.org/10.1023/A:1018980024795
Nash, M.A., Evans, C.: Warehouse order picking process at pelco products, Inc. In: Proceedings of the 2011 Industrial Engineering Research Conference, Reno, Nevada, USA, pp. 1–8 (2011)
Goetschalckx, M., Ashayeri, J.: Classification and design of order picking. Logist. World 2(2), 99–106 (1989)
Grosse, E.H., Glock, C.H., Jaber, M.Y., Neumann, W.P.: Incorporating human factors in order picking planning models: framework and research opportunities. Int. J. Prod. Res. 53(3), 695–717 (2015)
van Gils, T., Caris, A., Ramaekers, K., Braekers, K., de Koster, R.: Designing efficient order picking systems: the effect of real-life features on the relationship among planning problems. Transp. Res. Part E: Logist. Transp. Rev. 125, 47–73 (2019)
James, G., Witten, D., Hastie, T., Tibshirani, R.: An Introduction to Statistical Learning: with Applications in R. Springer Texts in Statistics. Springer, New York (2013). https://doi.org/10.1007/978-1-4614-7138-7
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 IFIP International Federation for Information Processing
About this paper
Cite this paper
Sloth, S.H., Bøgh, M.A., Nielsen, C.M., Konstantinidis, K.P., Sung, I. (2020). Data-Driven Replenishment Method Choice in a Picking System. In: Lalic, B., Majstorovic, V., Marjanovic, U., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. The Path to Digital Transformation and Innovation of Production Management Systems. APMS 2020. IFIP Advances in Information and Communication Technology, vol 591. Springer, Cham. https://doi.org/10.1007/978-3-030-57993-7_48
Download citation
DOI: https://doi.org/10.1007/978-3-030-57993-7_48
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-57992-0
Online ISBN: 978-3-030-57993-7
eBook Packages: Computer ScienceComputer Science (R0)
