Scheduling research contributions to Smart manufacturing

Autores
Rossit, Daniel Alejandro; Tohmé, Fernando Abel
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The incorporation of high technology to production systems is bringing the advent of Industry 4.0. One of the mainstays of Industry 4.0 is the application of Cyber-Physical Production Systems (CPPS). CPPSs will redefine decision-making processes in manufacturing environments, integrating traditionally disparate functionalities in a single system. One of the questions to be answered is how will the process of scheduling activities be redefined in this scenario. We examine the advances in the scheduling literature and analyze which aspects should be taken into account in future designs. Among them, we focus on topics as dynamic scheduling, distributed scheduling and inverse scheduling.
Fil: Rossit, Daniel Alejandro. 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. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina
Fil: Tohmé, Fernando Abel. 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. Universidad Nacional del Sur. Departamento de Economía; Argentina
Materia
Cyber-Physical Production Systems
Decision Making Process
Industry 4.0
Scheduling
Smart Manufacturing
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:11336/62101
Acceder
id CONICETDig_82ffdc658d00ef679652ba18782d4b07
oai_identifier_str oai:ri.conicet.gov.ar:11336/62101
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Scheduling research contributions to Smart manufacturingRossit, Daniel AlejandroTohmé, Fernando AbelCyber-Physical Production SystemsDecision Making ProcessIndustry 4.0SchedulingSmart Manufacturinghttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1The incorporation of high technology to production systems is bringing the advent of Industry 4.0. One of the mainstays of Industry 4.0 is the application of Cyber-Physical Production Systems (CPPS). CPPSs will redefine decision-making processes in manufacturing environments, integrating traditionally disparate functionalities in a single system. One of the questions to be answered is how will the process of scheduling activities be redefined in this scenario. We examine the advances in the scheduling literature and analyze which aspects should be taken into account in future designs. Among them, we focus on topics as dynamic scheduling, distributed scheduling and inverse scheduling.Fil: Rossit, Daniel Alejandro. 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. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Tohmé, Fernando Abel. 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. Universidad Nacional del Sur. Departamento de Economía; ArgentinaElsevier Ltd2018-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/62101Rossit, Daniel Alejandro; Tohmé, Fernando Abel; Scheduling research contributions to Smart manufacturing; Elsevier Ltd; Manufacturing Letters; 15; 1-2018; 111-1142213-8463CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://linkinghub.elsevier.com/retrieve/pii/S2213846317300871info:eu-repo/semantics/altIdentifier/doi/10.1016/j.mfglet.2017.12.005info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:50:58Zoai:ri.conicet.gov.ar:11336/62101instacron: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 14:50:59.041CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Scheduling research contributions to Smart manufacturing
title Scheduling research contributions to Smart manufacturing
spellingShingle Scheduling research contributions to Smart manufacturing
Rossit, Daniel Alejandro
Cyber-Physical Production Systems
Decision Making Process
Industry 4.0
Scheduling
Smart Manufacturing
title_short Scheduling research contributions to Smart manufacturing
title_full Scheduling research contributions to Smart manufacturing
title_fullStr Scheduling research contributions to Smart manufacturing
title_full_unstemmed Scheduling research contributions to Smart manufacturing
title_sort Scheduling research contributions to Smart manufacturing
dc.creator.none.fl_str_mv Rossit, Daniel Alejandro
Tohmé, Fernando Abel
author Rossit, Daniel Alejandro
author_facet Rossit, Daniel Alejandro
Tohmé, Fernando Abel
author_role author
author2 Tohmé, Fernando Abel
author2_role author
dc.subject.none.fl_str_mv Cyber-Physical Production Systems
Decision Making Process
Industry 4.0
Scheduling
Smart Manufacturing
topic Cyber-Physical Production Systems
Decision Making Process
Industry 4.0
Scheduling
Smart Manufacturing
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The incorporation of high technology to production systems is bringing the advent of Industry 4.0. One of the mainstays of Industry 4.0 is the application of Cyber-Physical Production Systems (CPPS). CPPSs will redefine decision-making processes in manufacturing environments, integrating traditionally disparate functionalities in a single system. One of the questions to be answered is how will the process of scheduling activities be redefined in this scenario. We examine the advances in the scheduling literature and analyze which aspects should be taken into account in future designs. Among them, we focus on topics as dynamic scheduling, distributed scheduling and inverse scheduling.
Fil: Rossit, Daniel Alejandro. 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. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina
Fil: Tohmé, Fernando Abel. 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. Universidad Nacional del Sur. Departamento de Economía; Argentina
description The incorporation of high technology to production systems is bringing the advent of Industry 4.0. One of the mainstays of Industry 4.0 is the application of Cyber-Physical Production Systems (CPPS). CPPSs will redefine decision-making processes in manufacturing environments, integrating traditionally disparate functionalities in a single system. One of the questions to be answered is how will the process of scheduling activities be redefined in this scenario. We examine the advances in the scheduling literature and analyze which aspects should be taken into account in future designs. Among them, we focus on topics as dynamic scheduling, distributed scheduling and inverse scheduling.
publishDate 2018
dc.date.none.fl_str_mv 2018-01
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/11336/62101
Rossit, Daniel Alejandro; Tohmé, Fernando Abel; Scheduling research contributions to Smart manufacturing; Elsevier Ltd; Manufacturing Letters; 15; 1-2018; 111-114
2213-8463
CONICET Digital
CONICET
url http://hdl.handle.net/11336/62101
identifier_str_mv Rossit, Daniel Alejandro; Tohmé, Fernando Abel; Scheduling research contributions to Smart manufacturing; Elsevier Ltd; Manufacturing Letters; 15; 1-2018; 111-114
2213-8463
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://linkinghub.elsevier.com/retrieve/pii/S2213846317300871
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.mfglet.2017.12.005
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
application/pdf
dc.publisher.none.fl_str_mv Elsevier Ltd
publisher.none.fl_str_mv Elsevier Ltd
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_ 1846083035244527616
score 13.22299

Publicaciones similares