Warehouse Management Systems (WMSs) record where products are stored in a physical warehouse; however, when pickers misplace products the WMS becomes misaligned with the real situation. Due to the fact that the WMS is not aware of these misalignments, it can lead pickers to empty shelves or shelves with the wrong and unexpected products. This paper proposes an extension to a WMS that tracks the state of the quality of the data and modifies picking reports based on this state to help pickers either avoid or discover these misalignments, depending on how it is configured. Using an experimental simulation to evaluate the approach, this paper shows how the solution can outperform a standalone WMS by approximately 1% when trying to avoid misalignments, and by approximately 32% when attempting to discover the misalignments.
|Title of host publication||ICIQ 2016: 21st International Conference on Information Quality|
|Place of Publication||Ciudad Real, Spain|
|Pages||1 - 12|
|Number of pages||12|
|Publication status||Published - 22 Jun 2016|
|Event||21st Conference on Information Quality - Cuidad Rel, Spain|
Duration: 22 Jun 2016 → 23 Jun 2016
|Conference||21st Conference on Information Quality|
|Abbreviated title||ICIQ 2016|
|Period||22/06/16 → 23/06/16|
Woodall, P., Giannikas, V., Lu, W., & McFarlane, D. (2016). Data State Tracking: labelling good quality data to improve warehouse operations. In ICIQ 2016: 21st International Conference on Information Quality (pp. 1 - 12). [Paper 13].