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dc.contributor.authorWang, Liping
dc.contributor.authorNie, Qingwei
dc.contributor.authorZhang, Zequn
dc.contributor.authorTang, Dunbing
dc.contributor.authorLiu, Changchun
dc.date.accessioned2024-12-24T19:02:52Z
dc.date.available2024-12-24T19:02:52Z
dc.date.copyright1/29/2024 12:00:00 AM
dc.date.issued2024
dc.identifier.issn1530-9827
dc.identifier.otherjcise_24_4_041008.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4303196
dc.description.abstractDue to the widespread adoption of personalized customization services, the application contexts within discrete manufacturing workshops have become increasingly intricate, necessitating the modern industry to evolve toward a more adaptable production trajectory. The pre-established production rules in a traditional centralized control manufacturing system present difficulties in accommodating dynamic situations. Although a multi-agent manufacturing system (MAMS) yields natural advantages in handling dynamic emergencies, the current research is limited to the computer simulation level and lacks integration with the underlying physical devices. In order to mitigate said challenges, the standardization modeling approach for the agent computing node (ACN) to facilitate the implementation of a readily deployable MAMS was proposed in the present study. Initially, adapters encompassing communication, decision, and control modules were developed within the industrial personnel computer-based computing node to accommodate the heterogeneous interface protocols of diverse machines. These adapters enable communication and interaction among machines while laying the computational foundation for the ACN. Accordingly, the models of the machine agent, the part agent, and the monitoring agent were constructed based on ACNs and could perceive the dynamic production information and support the enabling application. Subsequently, to guide ACNs in making scheduling decisions beneficial to global performance, an improved negotiation mechanism in MAMS was achieved in real-time. Finally, the proposed MAMS based on the ACN was deployed in an actual flexible machining workshop. Comparative experiments were implemented and, as exhibited from the experimental results, the proposed ACNs possessed the capabilities of achieving optimal global decision-making and facilitating straightforward deployment.
dc.publisherThe American Society of Mechanical Engineers (ASME)
dc.titleProbing an Easy-to-Deploy Multi-Agent Manufacturing System Based on Agent Computing Node: Architecture, Implementation, and Case Study
dc.typeJournal Paper
dc.journal.volume24
dc.journal.issue4
dc.journal.titleJournal of Computing and Information Science in Engineering
dc.identifier.doi10.1115/1.4064409
dc.journal.fristpage41008-1
dc.journal.lastpage41008-16
dc.page16
dc.treeJournal of Computing and Information Science in Engineering:;2024:;volume( 024 ):;issue: 004
dc.contenttypeFulltext


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