Location Management of Cloud Forklifts in Finished Product Warehouse. Issue 4 (26th October 2016)

• Record Type: Journal Article
• Authors: Zhao, Zhiheng; Fang, Ji; Huang, George Q.; Zhang, Mengdi
• Other Names: Chen Tin‐Chih Toly guestEditor.
• Is Part Of: International journal of intelligent systems. Volume 32:Issue 4(2017)
• Page Start: 342
• Page End: 370
• Publication Date: 2016-10-26
• Subjects: Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; 006.3
• DOI: 10.1002/int.21864
• Languages: English
• ISSNs: 0884-8173

Abstract

Abstract : The order picking process has been considered as the most time‐consuming and costly activity in warehouse management. Efficient location management, including product location management and storage location assignment management, serves as the key to reducing product searching time and traveling time during the process. This research is motivated by a real‐life industrial case, which is from a forklift manufacturer that encountered the underperformance in warehouse management. Excessive time was consumed in searching and picking the forklift in finished product warehouse, which thus led to great waste in resources and even the postponement of delivery. To solve this problem, this paper first presents the details about the problem and related processes. A conceptual model of cloud forklifts and its life cycle oriented management platform is then proposed. Accordingly, a prototype system named cloud forklift warehouse management system (CFWMS) is built based on the proposed model. The suggested model and system architecture is designed and developed with the commonality for general warehousing processes, and therefore can be easily configured and applied to any general warehouse environment. Results and details of implementation for the real‐life case are also provided to demonstrate the validity of the proposed model and CFWMS.