Managing an intelligent warehouse for a retail store with knowledge-driven approach | |
| Author | Tan, Chih-Fan |
| Call Number | AIT Thesis no.ISE-20-07 |
| Subject(s) | Stores, Retail--Management Warehouses--Automation |
| Note | A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Industrial and Manufacturing Engineering, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Abstract | The fourth industrial revolution is ongoing, and it changes the environment of retailer. For the retail store that directly serving final customer demand have some special characteristics and restrictions, such as varieties of goods yet limited space in a retail store, a customer order includes various products but each of them is with a small number of quantities, product with different feature like seasonal, etc. The competitiveness of the retail store relies on the utilization of the space and fulfillment of the customer demands. Data mining can explore the valuable information hidden in the high volume of data. Hence, how the retail store and warehouse can become intelligent by using historical shopping data of the customers for the warehouse operation decisions is a challenge. This research use data-driven approach to analyze historical customer order to unearth the relevance, customer buying behavior, time series, seasonal, etc. Then use knowledge-driven approach to define the class, property, relation between retail store, warehouse, and products, and let their knowledge can be shared, reused, and communicate in the company. Finally, via inference engine with semantic query enhanced web rule language to infer the correlation from a large amount of knowledge and find out the knowledge and logic which between concepts and attributes hidden in the ontology knowledge model; manager can through this inference to make the decision making. Therefore, this research use data-driven approach assists in knowledge-driven approach to manage the intelligent warehouse of the retail store. This research help retail stores quickly deliver the products and provide better service, and let the retail store and its warehouse can possess the ability to respond to the various changes. |
| Year | 2020 |
| Type | Thesis |
| School | School of Engineering and Technology (SET) |
| Department | Department of Industrial Systems Engineering (DISE) |
| Academic Program/FoS | Industrial Systems Engineering (ISE) |
| Chairperson(s) | Pisut Koomsap;Lin, Yu-Ju (Co-Chairperson) |
| Examination Committee(s) | Huang, Chin-Yin;Huynh Trung Luong |
| Degree | Thesis (M. Eng.) -- Asian Institute of Technology, 2020 |