Publication
Collective intelligence in self-organized industrial cyber-physical systems
| Summary: | Cyber-physical systems (CPS) play an important role in the implementation of new Industry 4.0 solutions, acting as the backbone infrastructure to host distributed intelligence capabilities and promote the collective intelligence that emerges from the interactions among individuals. This collective intelligence concept provides an alternative way to design complex systems with several benefits, such as modularity, flexibility, robustness, and reconfigurability to condition changes, but it also presents several challenges to be managed (e.g., non-linearity, self-organization, and myopia). With this in mind, this paper discusses the factors that characterize collective intelligence, particularly that associated with industrial CPS, analyzing the enabling concepts, technologies, and application sectors, and providing an illustrative example of its application in an automotive assembly line. The main contribution of the paper focuses on a comprehensive review and analysis of the main aspects, challenges, and research opportunities to be considered for implementing collective intelligence in industrial CPS. The identified challenges are clustered according to five different categories, namely decentralization, emergency, intelligent machines and products, infrastructures and methods, and human integration and ethics. Although the research indicates some potential benefits of using collective intelligence to achieve the desired levels of autonomy and dynamic adaptation of industrial CPS, such approaches are still in the early stages, with perspectives to increase in the coming years. Based on that, they need to be further developed considering some main aspects, for example, related to balancing the distribution of intelligence by the vertical and horizontal dimensions and controlling the nervousness in self-organized systems. |
|---|---|
| Main Authors: | Sakurada, Lucas |
| Other Authors: | Leitão, Paulo; Queiroz, Jonas |
| Subject: | Collective intelligence Cyber-physical systems Multi-agent systems Self-organization |
| Year: | 2022 |
| Country: | Portugal |
| Document type: | article |
| Access type: | open access |
| Associated institution: | Universidade Politécnica de Bragança |
| Language: | English |
| Origin: | Biblioteca Digital da UPB |
| _version_ | 1877782333534240768 |
|---|---|
| author | Sakurada, Lucas |
| author2 | Leitão, Paulo Queiroz, Jonas |
| author2_role | author author |
| author_facet | Sakurada, Lucas Leitão, Paulo Queiroz, Jonas |
| author_role | author |
| contributor_name_str_mv | Biblioteca Digital da UPB |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Sakurada, Lucas\"},{\"Person.name\":\"Leitão, Paulo\",\"Person.identifier.cienciaID\":\"8316-8F13-DA71\",\"Person.identifier.orcid\":\"0000-0002-2151-7944\",\"Person.identifier.scopusAuthorID\":\"35584388900\"},{\"Person.name\":\"Queiroz, Jonas\",\"Person.identifier.cienciaID\":\"BF12-BBDD-CCC5\",\"Person.identifier.orcid\":\"0000-0001-5416-4762\",\"Person.identifier.scopusAuthorID\":\"57188655139\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Biblioteca Digital da UPB |
| datacite.creators.creator.creatorName.fl_str_mv | Sakurada, Lucas Leitão, Paulo Queiroz, Jonas |
| datacite.date.Accepted.fl_str_mv | 2022-01-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2023-02-17T14:07:41Z |
| datacite.date.embargoed.fl_str_mv | 2023-02-17T14:07:41Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | Collective intelligence Cyber-physical systems Multi-agent systems Self-organization |
| datacite.titles.title.fl_str_mv | Collective intelligence in self-organized industrial cyber-physical systems |
| dc.contributor.none.fl_str_mv | Biblioteca Digital da UPB |
| dc.creator.none.fl_str_mv | Sakurada, Lucas Leitão, Paulo Queiroz, Jonas |
| dc.date.Accepted.fl_str_mv | 2022-01-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2023-02-17T14:07:41Z |
| dc.date.embargoed.fl_str_mv | 2023-02-17T14:07:41Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10198/27034 |
| dc.language.none.fl_str_mv | eng |
| dc.rights.cclincense.fl_str_mv | http://creativecommons.org/licenses/by/4.0/ |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | Collective intelligence Cyber-physical systems Multi-agent systems Self-organization |
| dc.title.fl_str_mv | Collective intelligence in self-organized industrial cyber-physical systems |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_6501 |
| description | Cyber-physical systems (CPS) play an important role in the implementation of new Industry 4.0 solutions, acting as the backbone infrastructure to host distributed intelligence capabilities and promote the collective intelligence that emerges from the interactions among individuals. This collective intelligence concept provides an alternative way to design complex systems with several benefits, such as modularity, flexibility, robustness, and reconfigurability to condition changes, but it also presents several challenges to be managed (e.g., non-linearity, self-organization, and myopia). With this in mind, this paper discusses the factors that characterize collective intelligence, particularly that associated with industrial CPS, analyzing the enabling concepts, technologies, and application sectors, and providing an illustrative example of its application in an automotive assembly line. The main contribution of the paper focuses on a comprehensive review and analysis of the main aspects, challenges, and research opportunities to be considered for implementing collective intelligence in industrial CPS. The identified challenges are clustered according to five different categories, namely decentralization, emergency, intelligent machines and products, infrastructures and methods, and human integration and ethics. Although the research indicates some potential benefits of using collective intelligence to achieve the desired levels of autonomy and dynamic adaptation of industrial CPS, such approaches are still in the early stages, with perspectives to increase in the coming years. Based on that, they need to be further developed considering some main aspects, for example, related to balancing the distribution of intelligence by the vertical and horizontal dimensions and controlling the nervousness in self-organized systems. |
| dirty | 0 |
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| language | eng |
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| person_str_mv | Sakurada, Lucas Leitão, Paulo Leitão, Paulo https://www.ciencia-id.pt/8316-8F13-DA71 8316-8F13-DA71 http://orcid.org/0000-0002-2151-7944 0000-0002-2151-7944 Queiroz, Jonas Queiroz, Jonas https://www.ciencia-id.pt/BF12-BBDD-CCC5 BF12-BBDD-CCC5 http://orcid.org/0000-0001-5416-4762 0000-0001-5416-4762 |
| publishDate | 2022 |
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| spelling | engpt_PTCyber-physical systems (CPS) play an important role in the implementation of new Industry 4.0 solutions, acting as the backbone infrastructure to host distributed intelligence capabilities and promote the collective intelligence that emerges from the interactions among individuals. This collective intelligence concept provides an alternative way to design complex systems with several benefits, such as modularity, flexibility, robustness, and reconfigurability to condition changes, but it also presents several challenges to be managed (e.g., non-linearity, self-organization, and myopia). With this in mind, this paper discusses the factors that characterize collective intelligence, particularly that associated with industrial CPS, analyzing the enabling concepts, technologies, and application sectors, and providing an illustrative example of its application in an automotive assembly line. The main contribution of the paper focuses on a comprehensive review and analysis of the main aspects, challenges, and research opportunities to be considered for implementing collective intelligence in industrial CPS. The identified challenges are clustered according to five different categories, namely decentralization, emergency, intelligent machines and products, infrastructures and methods, and human integration and ethics. Although the research indicates some potential benefits of using collective intelligence to achieve the desired levels of autonomy and dynamic adaptation of industrial CPS, such approaches are still in the early stages, with perspectives to increase in the coming years. Based on that, they need to be further developed considering some main aspects, for example, related to balancing the distribution of intelligence by the vertical and horizontal dimensions and controlling the nervousness in self-organized systems.application/pdfpt_PTCollective intelligence in self-organized industrial cyber-physical systemsSakurada, LucasPersonalLeitão, PauloDSpacehttp://dspace.org/items/68d9eb25-ad4f-439b-aeb2-35e8708644ccDSpacehttp://dspace.org/items/68d9eb25-ad4f-439b-aeb2-35e8708644ccLeitãoPauloCiência IDhttps://www.ciencia-id.pt8316-8F13-DA71ORCIDhttp://orcid.org0000-0002-2151-7944Scopus Author IDhttps://www.scopus.com35584388900PersonalQueiroz, JonasDSpacehttp://dspace.org/items/49c3a549-2500-4d74-8657-9d9baafffea3DSpacehttp://dspace.org/items/49c3a549-2500-4d74-8657-9d9baafffea3QueirozJonasCiência IDhttps://www.ciencia-id.ptBF12-BBDD-CCC5ORCIDhttp://orcid.org0000-0001-5416-4762Scopus Author IDhttps://www.scopus.com57188655139HostingInstitutionOrganizationalBiblioteca Digital da UPBe-mailmailto:dspace@unipb.ptdspace@unipb.ptDOIIsPartOf10.3390/electronics111932132023-02-17T14:07:41Z20222022-01-01T00:00:00ZHandlehttp://hdl.handle.net/10198/27034http://purl.org/coar/access_right/c_abf2open accessCollective intelligenceCyber-physical systemsMulti-agent systemsSelf-organization3489439 bytesliteraturehttp://purl.org/coar/resource_type/c_6501journal article2022http://creativecommons.org/licenses/by/4.0/http://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://bibliotecadigital.unipb.pt/bitstreams/59aa7634-5034-4da9-83d5-eae61ace6e68/downloadElectronics1119 |
| spellingShingle | Collective intelligence in self-organized industrial cyber-physical systems Sakurada, Lucas Collective intelligence Cyber-physical systems Multi-agent systems Self-organization |
| status | SINGLETON |
| subject.fl_str_mv | Collective intelligence Cyber-physical systems Multi-agent systems Self-organization |
| title | Collective intelligence in self-organized industrial cyber-physical systems |
| title_full | Collective intelligence in self-organized industrial cyber-physical systems |
| title_fullStr | Collective intelligence in self-organized industrial cyber-physical systems |
| title_full_unstemmed | Collective intelligence in self-organized industrial cyber-physical systems |
| title_short | Collective intelligence in self-organized industrial cyber-physical systems |
| title_sort | Collective intelligence in self-organized industrial cyber-physical systems |
| topic | Collective intelligence Cyber-physical systems Multi-agent systems Self-organization |
| topic_facet | Collective intelligence Cyber-physical systems Multi-agent systems Self-organization |
| url | http://hdl.handle.net/10198/27034 |
| visible | 1 |
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