Real-time order scheduling and execution monitoring in public warehouses based on radio frequency identification

Real-time order scheduling and execution monitoring in public warehouses based on radio frequency... The execution of storing and retrieval (R/S) orders in a public warehouse (PW) is very expensive because it tends to be either labor- or capital-intensive. How to economically and efficiently execute these orders is now becoming one of the most important issues for PWs in today’s competitive manufacturing environment. Therefore, by introducing RFID (radio frequency identification) technology into PWs, this paper proposes a RFID-based order scheduling and execution monitoring system (rfid-OSEMS) to address this issue. Firstly, the architecture of rfid-OSEMS is established, which can be divided into two correlative parts, including real-time order scheduling (RTOS) and RFID-based orders executing and monitoring (ROEM). Next, the RTOS model is put forward based on the concept of order group and the shortest path calculation. A genetic algorithm is employed to search for the optimal solution for RTOS. Then, the ROEM method is proposed based on the scheduling results of RTOS, wherein, four sub-models are discussed one by one, such as RFID configuration strategy (RFCS), RFID-based order executing (RFOE), real-time data collecting (RTDC), and RFID-based execution monitoring (RFEM). It not only shows how to execute R/S orders by integrating forklifts with RFID devices, but also reveals how to collect real-time data, what data should be collected, and how to use this collected data for monitoring. Finally, a use case is studied in a warehouse laboratory based on a prototype system which demonstrates the feasibility and applicability of the proposed methods and models. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The International Journal of Advanced Manufacturing Technology Springer Journals

Real-time order scheduling and execution monitoring in public warehouses based on radio frequency identification

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Publisher
Springer London
Copyright
Copyright © 2017 by Springer-Verlag London Ltd., part of Springer Nature
Subject
Engineering; Industrial and Production Engineering; Media Management; Mechanical Engineering; Computer-Aided Engineering (CAD, CAE) and Design
ISSN
0268-3768
eISSN
1433-3015
D.O.I.
10.1007/s00170-017-1381-z
Publisher site
See Article on Publisher Site

Abstract

The execution of storing and retrieval (R/S) orders in a public warehouse (PW) is very expensive because it tends to be either labor- or capital-intensive. How to economically and efficiently execute these orders is now becoming one of the most important issues for PWs in today’s competitive manufacturing environment. Therefore, by introducing RFID (radio frequency identification) technology into PWs, this paper proposes a RFID-based order scheduling and execution monitoring system (rfid-OSEMS) to address this issue. Firstly, the architecture of rfid-OSEMS is established, which can be divided into two correlative parts, including real-time order scheduling (RTOS) and RFID-based orders executing and monitoring (ROEM). Next, the RTOS model is put forward based on the concept of order group and the shortest path calculation. A genetic algorithm is employed to search for the optimal solution for RTOS. Then, the ROEM method is proposed based on the scheduling results of RTOS, wherein, four sub-models are discussed one by one, such as RFID configuration strategy (RFCS), RFID-based order executing (RFOE), real-time data collecting (RTDC), and RFID-based execution monitoring (RFEM). It not only shows how to execute R/S orders by integrating forklifts with RFID devices, but also reveals how to collect real-time data, what data should be collected, and how to use this collected data for monitoring. Finally, a use case is studied in a warehouse laboratory based on a prototype system which demonstrates the feasibility and applicability of the proposed methods and models.

Journal

The International Journal of Advanced Manufacturing TechnologySpringer Journals

Published: Nov 24, 2017

References

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