Volume 15 Number 2 (Mar. 2020)
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JSW 2020 Vol.15(2): 53-61 ISSN: 1796-217X
doi: 10.17706/jsw.15.2.53-61

Validating Time Efficiency of AOSR 2.0: A Novel WMS Planner Algorithm for SMEs, under Industry 4.0

Fareed Ud Din1*, David Paul2, Joe Ryan1, Frans Henskens1, Mark Wallis1
1The University of Newcastle, Callaghan, NSW, Australia
2 The University of New England, Armidale, NSW, Australia.

Abstract—Agent Oriented Storage and Retrieval (AOSR) WMS planner algorithm is a part of the general Agent Oriented Smart Factory (AOSF) framework, which provides a comprehensive Supply Chain (SC) architecture to help bridge the gap between Industry 4.0 standards and SME-oriented setups. This paper provides validation of AOSR algorithmwith respect to time efficiency on top of substantially improved performance efficiency in SME-oriented warehousing operations. This article, which is a part of a series of recent contributions, explains the efficiency of AOSR WMS planner algorithm in scenario-based test cases with experimentation in certain WMS Key Performance Indicators (KPIs).

Index Terms— Agent oriented smart factory (AOSF),small tomedium size enterprises (SMEs), cyber-physical systems (CPS),agent-orientedstorage and retrieval system (AOSR),warehouse management system (WMS)


Cite: Fareed Ud Din, David Paul, Joe Ryan, Frans Henskens, Mark Wallis, "Validating Time Efficiency of AOSR 2.0: A Novel WMS Planner Algorithm for SMEs, under Industry 4.0," Journal of Software vol. 15, no. 2 pp. 53-61, 2020.

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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