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Article: A roadmap for Assembly 4.0: self-configuration of fixed-position assembly islands under Graduation Intelligent Manufacturing System

TitleA roadmap for Assembly 4.0: self-configuration of fixed-position assembly islands under Graduation Intelligent Manufacturing System
Authors
KeywordsAssembly 4.0
intelligent manufacturing system
fixed-position assembly
self-configuration
cloud-based services
Issue Date2020
PublisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/00207543.asp
Citation
International Journal of Production Research, 2020, Epub 2020-05-20, p. 1-16 How to Cite?
AbstractThe layout of fixed-position assembly islands (FPAI) is widely used for producing fragile or bulky products. With the increasing customised demand and unique operation patterns, manufacturing practitioners are facing challenges on flexible and efficient production arrangement to meet customer demand, which lead to inappropriate assembly islands configuration, frequent setups and long waiting times in FPAI. Industry 4.0 comes with the promise of improved flexibility and efficiency in manufacturing. In the context of Industry 4.0, this paper proposes a 5-layer APICS (assembly layer, perception layer, interaction layer, cognition layer, and service layer) roadmap for transformation and implementation of Assembly 4.0. Following the 5-layer APICS roadmap, a Graduation Intelligent Manufacturing System (GiMS) is presented as the pioneering implementation in FPAI. A graduation-inspired assembly system is designed for FPAI at assembly layer. Internet of Things (IoT) and industrial wearable technologies are deployed for perception, connection, and collaboration among various manufacturing resources at perception and interaction layer. A self-configuration model is proposed at cognition layer for autonomously configuring optimal assembly islands and corresponding production activities to meet customer demand. Cloud-based services are developed for managers and onsite operators to facilitate their decision-making and daily operations at service layer. Finally, a demonstrative case is conducted to verify the feasibility of the proposed methods.
DescriptionLink to Free access
Persistent Identifierhttp://hdl.handle.net/10722/283047
ISSN
2023 Impact Factor: 7.0
2023 SCImago Journal Rankings: 2.668
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorGUO, D-
dc.contributor.authorZhong, RY-
dc.contributor.authorLING, S-
dc.contributor.authorRong, Y-
dc.contributor.authorHuang, GQ-
dc.date.accessioned2020-06-05T06:24:21Z-
dc.date.available2020-06-05T06:24:21Z-
dc.date.issued2020-
dc.identifier.citationInternational Journal of Production Research, 2020, Epub 2020-05-20, p. 1-16-
dc.identifier.issn0020-7543-
dc.identifier.urihttp://hdl.handle.net/10722/283047-
dc.descriptionLink to Free access-
dc.description.abstractThe layout of fixed-position assembly islands (FPAI) is widely used for producing fragile or bulky products. With the increasing customised demand and unique operation patterns, manufacturing practitioners are facing challenges on flexible and efficient production arrangement to meet customer demand, which lead to inappropriate assembly islands configuration, frequent setups and long waiting times in FPAI. Industry 4.0 comes with the promise of improved flexibility and efficiency in manufacturing. In the context of Industry 4.0, this paper proposes a 5-layer APICS (assembly layer, perception layer, interaction layer, cognition layer, and service layer) roadmap for transformation and implementation of Assembly 4.0. Following the 5-layer APICS roadmap, a Graduation Intelligent Manufacturing System (GiMS) is presented as the pioneering implementation in FPAI. A graduation-inspired assembly system is designed for FPAI at assembly layer. Internet of Things (IoT) and industrial wearable technologies are deployed for perception, connection, and collaboration among various manufacturing resources at perception and interaction layer. A self-configuration model is proposed at cognition layer for autonomously configuring optimal assembly islands and corresponding production activities to meet customer demand. Cloud-based services are developed for managers and onsite operators to facilitate their decision-making and daily operations at service layer. Finally, a demonstrative case is conducted to verify the feasibility of the proposed methods.-
dc.languageeng-
dc.publisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/00207543.asp-
dc.relation.ispartofInternational Journal of Production Research-
dc.rightsAOM/Preprint Before Accepted: his article has been accepted for publication in [JOURNAL TITLE], published by Taylor & Francis. AOM/Preprint After Accepted: This is an [original manuscript / preprint] of an article published by Taylor & Francis in [JOURNAL TITLE] on [date of publication], available online: http://www.tandfonline.com/[Article DOI]. Accepted Manuscript (AM) i.e. Postprint This is an Accepted Manuscript of an article published by Taylor & Francis in [JOURNAL TITLE] on [date of publication], available online: http://www.tandfonline.com/[Article DOI].-
dc.subjectAssembly 4.0-
dc.subjectintelligent manufacturing system-
dc.subjectfixed-position assembly-
dc.subjectself-configuration-
dc.subjectcloud-based services-
dc.titleA roadmap for Assembly 4.0: self-configuration of fixed-position assembly islands under Graduation Intelligent Manufacturing System-
dc.typeArticle-
dc.identifier.emailZhong, RY: zhongzry@hku.hk-
dc.identifier.emailHuang, GQ: gqhuang@hku.hk-
dc.identifier.authorityZhong, RY=rp02116-
dc.identifier.authorityHuang, GQ=rp00118-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/00207543.2020.1762944-
dc.identifier.scopuseid_2-s2.0-85085482720-
dc.identifier.hkuros310054-
dc.identifier.volumeEpub 2020-05-20-
dc.identifier.spage1-
dc.identifier.epage16-
dc.identifier.isiWOS:000536978100001-
dc.publisher.placeUnited Kingdom-
dc.identifier.issnl0020-7543-

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