Scheduling in cloud manufacturing systems: Recent systematic literature review

Autores
Halty, Agustín; Sánchez, Rodrigo; Vázquez, Valentín; Viana, Víctor; Piñeyro, Pedro; Rossit, Daniel Alejandro
Año de publicación
2020
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Cloud Manufacturing (CMFg) is a novel production paradigm that benefits from Cloud Computing in order to develop manufacturing systems linked by the cloud. These systems, based on virtual platforms, allow direct linkage between customers and suppliers of manufacturing services, regardless of geographical distance. In this way, CMfg can expand both markets for producers, and suppliers for customers. However, these linkages imply a new challenge for production planning and decision-making process, especially in Scheduling. In this paper, a systematic literature review of articles addressing scheduling in Cloud Manufacturing environments is carried out. The review takes as its starting point a seminal study published in 2019, in which all problem features are described in detail. We pay special attention to the optimization methods and problem-solving strategies that have been suggested in CMfg scheduling. From the review carried out, we can assert that CMfg is a topic of growing interest within the scientific community. We also conclude that the methods based on bio-inspired metaheuristics are by far the most widely used (they represent more than 50% of the articles found). On the other hand, we suggest some lines for future research to further consolidate this field. In particular, we want to highlight the multi-objective approach, since due to the nature of the problem and the production paradigm, the optimization objectives involved are generally in conflict. In addition, decentralized approaches such as those based on game theory are promising lines for future research.
Fil: Halty, Agustín. Universidad de la República; Uruguay
Fil: Sánchez, Rodrigo. Universidad de la República; Uruguay
Fil: Vázquez, Valentín. Universidad de la República; Uruguay
Fil: Viana, Víctor. Universidad de la República; Uruguay
Fil: Piñeyro, Pedro. Universidad de la República; Uruguay
Fil: Rossit, Daniel Alejandro. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina
Materia
CLOUD COMPUTING
CLOUD MANUFACTURING
CYBER-PHYSICAL SYSTEMS
INDUSTRY 4.0
INTERNET OF THINGS
LITERATURE REVIEW
MULTI-OBJECTIVE
OPTIMIZATION
SCHEDULING
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/124528
Acceder
id CONICETDig_bc64345a4d9d19fcdee9ec6450e32962
oai_identifier_str oai:ri.conicet.gov.ar:11336/124528
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Scheduling in cloud manufacturing systems: Recent systematic literature reviewHalty, AgustínSánchez, RodrigoVázquez, ValentínViana, VíctorPiñeyro, PedroRossit, Daniel AlejandroCLOUD COMPUTINGCLOUD MANUFACTURINGCYBER-PHYSICAL SYSTEMSINDUSTRY 4.0INTERNET OF THINGSLITERATURE REVIEWMULTI-OBJECTIVEOPTIMIZATIONSCHEDULINGhttps://purl.org/becyt/ford/2.11https://purl.org/becyt/ford/2Cloud Manufacturing (CMFg) is a novel production paradigm that benefits from Cloud Computing in order to develop manufacturing systems linked by the cloud. These systems, based on virtual platforms, allow direct linkage between customers and suppliers of manufacturing services, regardless of geographical distance. In this way, CMfg can expand both markets for producers, and suppliers for customers. However, these linkages imply a new challenge for production planning and decision-making process, especially in Scheduling. In this paper, a systematic literature review of articles addressing scheduling in Cloud Manufacturing environments is carried out. The review takes as its starting point a seminal study published in 2019, in which all problem features are described in detail. We pay special attention to the optimization methods and problem-solving strategies that have been suggested in CMfg scheduling. From the review carried out, we can assert that CMfg is a topic of growing interest within the scientific community. We also conclude that the methods based on bio-inspired metaheuristics are by far the most widely used (they represent more than 50% of the articles found). On the other hand, we suggest some lines for future research to further consolidate this field. In particular, we want to highlight the multi-objective approach, since due to the nature of the problem and the production paradigm, the optimization objectives involved are generally in conflict. In addition, decentralized approaches such as those based on game theory are promising lines for future research.Fil: Halty, Agustín. Universidad de la República; UruguayFil: Sánchez, Rodrigo. Universidad de la República; UruguayFil: Vázquez, Valentín. Universidad de la República; UruguayFil: Viana, Víctor. Universidad de la República; UruguayFil: Piñeyro, Pedro. Universidad de la República; UruguayFil: Rossit, Daniel Alejandro. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; ArgentinaAmerican Institute of Mathematical Sciences2020-10-28info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/124528Halty, Agustín; Sánchez, Rodrigo; Vázquez, Valentín; Viana, Víctor; Piñeyro, Pedro; et al.; Scheduling in cloud manufacturing systems: Recent systematic literature review; American Institute of Mathematical Sciences; Mathematical Biosciences And Engineering; 17; 6; 28-10-2020; 7378-73971551-0018CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.aimspress.com/article/10.3934/mbe.2020377info:eu-repo/semantics/altIdentifier/doi/10.3934/mbe.2020377info:eu-repo/semantics/altIdentifier/url/http://www.aimspress.com/mbe/article/5911/special-articlesinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:43:59Zoai:ri.conicet.gov.ar:11336/124528instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 14:43:59.536CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Scheduling in cloud manufacturing systems: Recent systematic literature review
title Scheduling in cloud manufacturing systems: Recent systematic literature review
spellingShingle Scheduling in cloud manufacturing systems: Recent systematic literature review
Halty, Agustín
CLOUD COMPUTING
CLOUD MANUFACTURING
CYBER-PHYSICAL SYSTEMS
INDUSTRY 4.0
INTERNET OF THINGS
LITERATURE REVIEW
MULTI-OBJECTIVE
OPTIMIZATION
SCHEDULING
title_short Scheduling in cloud manufacturing systems: Recent systematic literature review
title_full Scheduling in cloud manufacturing systems: Recent systematic literature review
title_fullStr Scheduling in cloud manufacturing systems: Recent systematic literature review
title_full_unstemmed Scheduling in cloud manufacturing systems: Recent systematic literature review
title_sort Scheduling in cloud manufacturing systems: Recent systematic literature review
dc.creator.none.fl_str_mv Halty, Agustín
Sánchez, Rodrigo
Vázquez, Valentín
Viana, Víctor
Piñeyro, Pedro
Rossit, Daniel Alejandro
author Halty, Agustín
author_facet Halty, Agustín
Sánchez, Rodrigo
Vázquez, Valentín
Viana, Víctor
Piñeyro, Pedro
Rossit, Daniel Alejandro
author_role author
author2 Sánchez, Rodrigo
Vázquez, Valentín
Viana, Víctor
Piñeyro, Pedro
Rossit, Daniel Alejandro
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv CLOUD COMPUTING
CLOUD MANUFACTURING
CYBER-PHYSICAL SYSTEMS
INDUSTRY 4.0
INTERNET OF THINGS
LITERATURE REVIEW
MULTI-OBJECTIVE
OPTIMIZATION
SCHEDULING
topic CLOUD COMPUTING
CLOUD MANUFACTURING
CYBER-PHYSICAL SYSTEMS
INDUSTRY 4.0
INTERNET OF THINGS
LITERATURE REVIEW
MULTI-OBJECTIVE
OPTIMIZATION
SCHEDULING
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.11
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Cloud Manufacturing (CMFg) is a novel production paradigm that benefits from Cloud Computing in order to develop manufacturing systems linked by the cloud. These systems, based on virtual platforms, allow direct linkage between customers and suppliers of manufacturing services, regardless of geographical distance. In this way, CMfg can expand both markets for producers, and suppliers for customers. However, these linkages imply a new challenge for production planning and decision-making process, especially in Scheduling. In this paper, a systematic literature review of articles addressing scheduling in Cloud Manufacturing environments is carried out. The review takes as its starting point a seminal study published in 2019, in which all problem features are described in detail. We pay special attention to the optimization methods and problem-solving strategies that have been suggested in CMfg scheduling. From the review carried out, we can assert that CMfg is a topic of growing interest within the scientific community. We also conclude that the methods based on bio-inspired metaheuristics are by far the most widely used (they represent more than 50% of the articles found). On the other hand, we suggest some lines for future research to further consolidate this field. In particular, we want to highlight the multi-objective approach, since due to the nature of the problem and the production paradigm, the optimization objectives involved are generally in conflict. In addition, decentralized approaches such as those based on game theory are promising lines for future research.
Fil: Halty, Agustín. Universidad de la República; Uruguay
Fil: Sánchez, Rodrigo. Universidad de la República; Uruguay
Fil: Vázquez, Valentín. Universidad de la República; Uruguay
Fil: Viana, Víctor. Universidad de la República; Uruguay
Fil: Piñeyro, Pedro. Universidad de la República; Uruguay
Fil: Rossit, Daniel Alejandro. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina
description Cloud Manufacturing (CMFg) is a novel production paradigm that benefits from Cloud Computing in order to develop manufacturing systems linked by the cloud. These systems, based on virtual platforms, allow direct linkage between customers and suppliers of manufacturing services, regardless of geographical distance. In this way, CMfg can expand both markets for producers, and suppliers for customers. However, these linkages imply a new challenge for production planning and decision-making process, especially in Scheduling. In this paper, a systematic literature review of articles addressing scheduling in Cloud Manufacturing environments is carried out. The review takes as its starting point a seminal study published in 2019, in which all problem features are described in detail. We pay special attention to the optimization methods and problem-solving strategies that have been suggested in CMfg scheduling. From the review carried out, we can assert that CMfg is a topic of growing interest within the scientific community. We also conclude that the methods based on bio-inspired metaheuristics are by far the most widely used (they represent more than 50% of the articles found). On the other hand, we suggest some lines for future research to further consolidate this field. In particular, we want to highlight the multi-objective approach, since due to the nature of the problem and the production paradigm, the optimization objectives involved are generally in conflict. In addition, decentralized approaches such as those based on game theory are promising lines for future research.
publishDate 2020
dc.date.none.fl_str_mv 2020-10-28
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/124528
Halty, Agustín; Sánchez, Rodrigo; Vázquez, Valentín; Viana, Víctor; Piñeyro, Pedro; et al.; Scheduling in cloud manufacturing systems: Recent systematic literature review; American Institute of Mathematical Sciences; Mathematical Biosciences And Engineering; 17; 6; 28-10-2020; 7378-7397
1551-0018
CONICET Digital
CONICET
url http://hdl.handle.net/11336/124528
identifier_str_mv Halty, Agustín; Sánchez, Rodrigo; Vázquez, Valentín; Viana, Víctor; Piñeyro, Pedro; et al.; Scheduling in cloud manufacturing systems: Recent systematic literature review; American Institute of Mathematical Sciences; Mathematical Biosciences And Engineering; 17; 6; 28-10-2020; 7378-7397
1551-0018
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.aimspress.com/article/10.3934/mbe.2020377
info:eu-repo/semantics/altIdentifier/doi/10.3934/mbe.2020377
info:eu-repo/semantics/altIdentifier/url/http://www.aimspress.com/mbe/article/5911/special-articles
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv American Institute of Mathematical Sciences
publisher.none.fl_str_mv American Institute of Mathematical Sciences
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1846082948270391296
score 13.221938

Publicaciones similares