Introduction of a real time location system to enhance the warehouse safety and operational efficiency

被引:54
作者
Halawa, Farouq [1 ]
Dauod, Husam [1 ]
Lee, In Gyu [1 ]
Li, Yinglei [2 ]
Yoon, Sang Won [1 ]
Chung, Sung Hoon [1 ]
机构
[1] SUNY Binghamton, Dept Syst Sci & Ind Engn, Binghamton, NY 13902 USA
[2] Breakthrough Fuel, Green Bay, WI USA
关键词
Real-time location system; Industry; 4.0; Data analytics; Warehouse management system; Ultra-wide band; RESOURCE-MANAGEMENT SYSTEM; CONGESTION; PICKERS;
D O I
10.1016/j.ijpe.2019.107541
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
As a real time location system (RTLS) can provide positioning and tracking of forklifts and other mobile entities in a warehouse, the integration of RTLS into a data system has a significant potential to enhance safety and improve efficiency. The objective of this research is to demonstrate how RTLS technology can be leveraged to enhance the warehouse safety and operational efficiency via a real warehouse case study. The research is implemented using a novel three-phase framework to introduce the RTLS technology in the warehouse. The first phase evaluates available RTLS technologies. Market research has been conducted to compare different RTLS technologies, and the outcome of this phase suggests that the ultra-wide band (UWB) is the best technology for indoor positioning and tracking in the warehouse with respect to several metrics. The second phase is the technology implementation, which aims to integrate RTLS with other existing warehouse operation systems, i.e., the warehouse management system (WMS) and the forklift fleet management system (FFMS). In this phase, light is shed on current challenges and proposed solutions of RTLS data accuracy and synchronization. The final phase is post-implementation, in which several methods and data visualization tools are proposed to tackle safety and operational issues. A real warehouse in the US has been used as a case study to evaluate the proposed framework. In particular, the following analyses have been conducted using the actual RTLS data: (1) harshness in braking, (2) compliance to routing policies, (3) driver patterns in intersections, (4) congestion identification and prevention, (5) speed per zone, (6) impact analysis, and (7) faults analysis. The results suggest that the proposed framework has a great potential to advance the current warehouse solutions one step forward to realize smart warehouse operations.
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页数:21
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