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A RFID-based storage assignment system for enhancing the efficiency of order picking
- Source :
- Journal of Intelligent Manufacturing. 28:111-129
- Publication Year :
- 2014
- Publisher :
- Springer Science and Business Media LLC, 2014.
-
Abstract
- In today's time-sensitive markets, effective storage policies are widely accepted as a means for improving the efficiency of order picking. As a result of customization, the variety of products handled by a warehouse has increased, making storage location assignment problems more complicated. Different approaches have been proposed by researchers for improving storage assignment and order picking. However, many industrial practitioners find it difficult to adopt such approaches due to complexity and high associated costs. In particular, small and medium enterprises (SMEs), that generally, lack resources and who have staff members with weak artificial intelligence backgrounds, still rely on experience when assigning storage locations for diverse products. In these circumstances, the quality of decision making cannot be guaranteed. In view of this, an intelligent system which can be easily adopted by SMEs is designed to improve storage location assignment problems. The proposed system, an RFID-based storage assignment system (RFID-SAS), is a rule-based system incorporating radio frequency identification (RFID) provides decision support for storage assignment in a warehouse. Unlike many existing situations, RFID tags are attached to products at the item level instead of at the pallet level. As the knowledge embedded in the system is represented in the form of rules, evaluation is important and is outlined in this paper. The effectiveness of the system is verified by means of a case study in which the system is implemented in a typical SME specializing in machinery manufacturing. The results illustrate that RFID-SAS can enhance the efficiency of order picking in a warehouse.
- Subjects :
- 0209 industrial biotechnology
Engineering drawing
Order picking
Engineering
Decision support system
business.industry
media_common.quotation_subject
02 engineering and technology
Industrial engineering
Industrial and Manufacturing Engineering
Variety (cybernetics)
Personalization
020901 industrial engineering & automation
Artificial Intelligence
0202 electrical engineering, electronic engineering, information engineering
Radio-frequency identification
020201 artificial intelligence & image processing
Quality (business)
Small and medium-sized enterprises
Pallet
business
Software
media_common
Subjects
Details
- ISSN :
- 15728145 and 09565515
- Volume :
- 28
- Database :
- OpenAIRE
- Journal :
- Journal of Intelligent Manufacturing
- Accession number :
- edsair.doi...........8b8370e621aa000af016e8f1eb5a6c74
- Full Text :
- https://doi.org/10.1007/s10845-014-0965-9