University of Twente Student Theses
Improving Decision Making in Warehouse : Data-Driven Forecasting and Storage Simulation
Li, Jiayu (2023) Improving Decision Making in Warehouse : Data-Driven Forecasting and Storage Simulation.
|
PDF
7MB |
| Abstract: | The thesis presents a data-driven solution that utilises a data warehouse and several software tools to help decision making in warehousing business. The solution consists of the forecasting service and the storage simulator service. In warehousing, forecasting is often desired to predict the daily workload to meet the demand for picking and to have an appropriate number of workers available for the day. Storage policy is a method to allocate products in different sections of the storage primarily based on their demand in order for pickers to reach these products faster. Forecasting the picking demand with higher accuracy and choosing a suitable storage policy help improve efficiency and reduce costs in warehousing operations. We illustrated how these two services are realised with an architecture based on a data warehouse. Use cases of the services were created to help warehousing managers and supervisors make improved data-driven decisions. |
| Item Type: | Essay (Master) |
| Clients: | Bricklog, Apeldoorn |
| Faculty: | EEMCS: Electrical Engineering, Mathematics and Computer Science |
| Subject: | 50 technical science in general |
| Programme: | Business Information Technology MSc (60025) |
| Link to this item: | https://purl.utwente.nl/essays/97666 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
Show download statistics for this publication
Show download statistics for this publicationRepository Staff Only: item control page