Title: AOSR: an agent oriented storage and retrieval WMS planner for SMEs, associated with AOSF framework, under Industry 4.0

Authors: Fareed Ud Din; David Paul; Frans Henskens; Mark Wallis; Muhammad Adnan Hashmi

Addresses: School of Science and Technology, The University of New England, Armidale, NSW, Australia ' School of Science and Technology, The University of New England, Armidale, NSW, Australia ' School of Electrical Engineering and Computing, The University of Newcastle, Callaghan, NSW, Australia ' School of Electrical Engineering and Computing, The University of Newcastle, Callaghan, NSW, Australia ' Department of Computer Science and IT, The University of Lahore, Punjab, Lahore, Pakistan

Abstract: The concept of a smart factory, under Industry 4.0 relies heavily on cyber physical systems (CPS) and intra-enterprise-wide-networks (IWN). Cloud-based implementation is incumbent to accomplish the promises of enterprise integration, automation, seamless information exchange and intelligent self-organisation. Extensive research has been conducted in this domain, however, there is still much research to be done from the perspective of such frameworks in small to medium size enterprises (SMEs). In this context, the agent-oriented smart factory (AOSF) framework provides a generic end-to-end supply chain (SC) model, compliant with CPS and Industry 4.0 standards. In order to support the crucial side of warehouse management, this paper presents AOSF's recommended agent-oriented storage and retrieval (AOSR) warehouse planner with hybrid logic-based strategy, which yields a smart time-stamped plan to manage product placement and retrieval efficiently. The AOSF-associated AOSR-planner uses the hierarchical task network (HTN) AI planning to ensure different warehouse operations in a timely manner.

Keywords: smart factory; small to medium size enterprises; SMEs; agent-oriented storage and retrieval system; AOSR; agent-oriented smart factory; AOSF; warehouse management system; WMS; enterprise integration; EI; supply chain; SC.

DOI: 10.1504/IJADS.2022.125487

International Journal of Applied Decision Sciences, 2022 Vol.15 No.5, pp.641 - 661

Received: 22 Feb 2021
Accepted: 11 Jun 2021
Published online: 12 Sep 2022 *

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