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Development of a warehouse slotting model to improve picking performance


Development of a warehouse slotting model to improve picking performance

Khullar, Chirag (2021) Development of a warehouse slotting model to improve picking performance. Masters thesis, Concordia University.

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Congestion during picking operations in warehouse with mixed aisles (narrow aisles and wide aisles) has rarely been studied in current literature in the context of warehouse slotting (i.e. arrangement of inventory in warehouse). This study aims at improving the picking efficiency of the Asmodee Canada Inc. warehouse. Using a combination of clustering slotting heuristics and popularity-based slotting heuristics, a re-slotting policy was developed. Furthermore, to provide a robust re-slotting with limited number of items moves, a healing technique based on urgency score was developed. Use of a process control chart to monitor the picking performance of Asmodee’s warehouse and hence to signal healing was suggested. Using picking simulation, we find that when the re-slotting heuristics is used, there is substantial reduction in distance travelled of up to 29% and waiting times due to congestion can be reduced by as much as 85%. The healing technique also decreased distance travelled and waiting times. However, as the number of items moved in healing constitute on average less than 5% of the items, such improvements are limited. The distance traveled was reduced by as high as 9.4% in some aggregated orders and waiting time reduction was as high as 29.1%. The techniques developed in this paper will help Asmodee Canada Inc. in improving their picking operations. It will also help to build better strategies for warehouses having mixed aisles, where in aisle congestion is an issue to consider while re-slotting.

Divisions:Concordia University > John Molson School of Business > Supply Chain and Business Technology Management
Item Type:Thesis (Masters)
Authors:Khullar, Chirag
Institution:Concordia University
Degree Name:M.S.C.M.
Program:Supply Chain Management
Date:28 July 2021
Thesis Supervisor(s):Satir, Ahmet and S. Chauhan, Satyaveer
Keywords:Warehousing, SKU Slotting, Order Picking, Picking Frequency, Item Affinity, Clustering, Healing, Urgency Score, Heuristic, Process Control Chart.
ID Code:988612
Deposited By: Chirag Khullar
Deposited On:29 Nov 2021 16:57
Last Modified:29 Nov 2021 16:57


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