Modelo fuzzy cascata multiatributos e preditivo para despacho de AGVs em FMS

Detalhes bibliográficos
Autor(a) principal: Caridá, Vinicius Fernandes
Data de Publicação: 2016
Tipo de documento: Tese
Idioma: por
Título da fonte: Repositório Institucional da UFSCAR
Texto Completo: https://repositorio.ufscar.br/handle/ufscar/7985
Resumo: In recent years, manufacturers are increasingly applying automation techniques with the aim of increase their efficiency to remain competitive. The material handling is an essential activity in any process of production and its effectiveness has severe impacts on production costs. Systems of automated guided vehicles (AGVs) have become an important strategic tool for factories and automated warehouses. In a very competitive business scenario, they can increase productivity and reduce costs. The management of these AGVs is the key to a transport system that ensures the improvements envisioned by the industry. One of the main problems encountered in the management of AGVs is the dispatch decision. This paper proposes a vehicles dispatch model based on a fuzzy cascade system for consideration of multiple attributes of the factory and a structure based on state space that enables the extraction of information of future states of the industrial production system. The objective is to reduce makespan and tardiness values of the production system. Two factory scenarios are simulated and tests are performed of the model and five other methods of dispatch. A statistical validation is realized of the results in which corroborates with 97% confidence the hypotheses of the work.
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spelling Caridá, Vinicius FernandesMorandin Júnior, Orideshttp://lattes.cnpq.br/4192845106907956http://lattes.cnpq.br/084332816305278876502433-7770-4536-a688-c0013d4f59602016-10-20T18:15:28Z2016-10-20T18:15:28Z2016-05-02CARIDÁ, Vinicius Fernandes. Modelo fuzzy cascata multiatributos e preditivo para despacho de AGVs em FMS. 2016. Tese (Doutorado em Ciência da Computação) – Universidade Federal de São Carlos, São Carlos, 2016. Disponível em: https://repositorio.ufscar.br/handle/ufscar/7985.https://repositorio.ufscar.br/handle/ufscar/7985In recent years, manufacturers are increasingly applying automation techniques with the aim of increase their efficiency to remain competitive. The material handling is an essential activity in any process of production and its effectiveness has severe impacts on production costs. Systems of automated guided vehicles (AGVs) have become an important strategic tool for factories and automated warehouses. In a very competitive business scenario, they can increase productivity and reduce costs. The management of these AGVs is the key to a transport system that ensures the improvements envisioned by the industry. One of the main problems encountered in the management of AGVs is the dispatch decision. This paper proposes a vehicles dispatch model based on a fuzzy cascade system for consideration of multiple attributes of the factory and a structure based on state space that enables the extraction of information of future states of the industrial production system. The objective is to reduce makespan and tardiness values of the production system. Two factory scenarios are simulated and tests are performed of the model and five other methods of dispatch. A statistical validation is realized of the results in which corroborates with 97% confidence the hypotheses of the work.Nos últimos anos, as indústrias vêm cada vez mais aplicando técnicas de automação com o objetivo de aumentar sua eficiência para manterem-se competitivas. O manuseio de materiais é uma atividade essencial em qualquer processo de produção e sua eficácia tem impactos severos sobre os custos de produção. Sistemas de veículos autoguiados (AGVs) tornaram-se uma ferramenta estratégica importante para fábricas e armazéns automatizados. Em um cenário de negócio muito competitivo, eles podem aumentar a produtividade e reduzir os custos. O gerenciamento desses AGVs é a chave para um sistema de transporte que garanta as melhorias vislumbradas pelas indústrias. Um dos principais problemas encontrados no gerenciamento dos AGVs é a decisão de despacho. Esse trabalho propõe um modelo de despacho de veículos baseado em um sistema fuzzy cascata para ponderação de múltiplos atributos da fábrica e em uma estrutura baseada em espaço de estados que permita a extração de informações de estados futuros do sistema de produção fabril. O objetivo é reduzir valores de makespan e tardiness do sistema de produção. Dois cenários de fábrica são simulados e são realizados testes do modelo proposto e cinco outros métodos de despachos. É realizada uma validação estatística dos resultados em que se corrobora com 97% de confiança as hipóteses do trabalhoporUniversidade Federal de São CarlosCâmpus São CarlosPrograma de Pós-Graduação em Ciência da Computação - PPGCCUFSCarFuzzy logicPredictionAutomated Guided VehicletemsAutomated Guided VehicleAGV controlDespacho de AGVsInteligência artificialSistemas flexíveis de manufaturaCIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::SISTEMAS DE COMPUTACAOModelo fuzzy cascata multiatributos e preditivo para despacho de AGVs em FMSinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisOnline600600699c22db-73af-4a67-a1af-0c10448ea48binfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFSCARinstname:Universidade Federal de São Carlos (UFSCAR)instacron:UFSCARORIGINALTeseVFC.pdfTeseVFC.pdfapplication/pdf9165002https://repositorio.ufscar.br/bitstream/ufscar/7985/1/TeseVFC.pdfbb98f82058344c51fda9b34979b8a524MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81957https://repositorio.ufscar.br/bitstream/ufscar/7985/2/license.txtae0398b6f8b235e40ad82cba6c50031dMD52TEXTTeseVFC.pdf.txtTeseVFC.pdf.txtExtracted texttext/plain316735https://repositorio.ufscar.br/bitstream/ufscar/7985/3/TeseVFC.pdf.txt7286a6976d450895c4ac73e83d270ecfMD53THUMBNAILTeseVFC.pdf.jpgTeseVFC.pdf.jpgIM Thumbnailimage/jpeg7885https://repositorio.ufscar.br/bitstream/ufscar/7985/4/TeseVFC.pdf.jpg589f2ac9b0a99463c732a01ef986c085MD54ufscar/79852023-09-18 18:31:01.039oai:repositorio.ufscar.br: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Repositório InstitucionalPUBhttps://repositorio.ufscar.br/oai/requestopendoar:43222023-09-18T18:31:01Repositório Institucional da UFSCAR - Universidade Federal de São Carlos (UFSCAR)false
dc.title.por.fl_str_mv Modelo fuzzy cascata multiatributos e preditivo para despacho de AGVs em FMS
title Modelo fuzzy cascata multiatributos e preditivo para despacho de AGVs em FMS
spellingShingle Modelo fuzzy cascata multiatributos e preditivo para despacho de AGVs em FMS
Caridá, Vinicius Fernandes
Fuzzy logic
Prediction
Automated Guided Vehicletems
Automated Guided Vehicle
AGV control
Despacho de AGVs
Inteligência artificial
Sistemas flexíveis de manufatura
CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::SISTEMAS DE COMPUTACAO
title_short Modelo fuzzy cascata multiatributos e preditivo para despacho de AGVs em FMS
title_full Modelo fuzzy cascata multiatributos e preditivo para despacho de AGVs em FMS
title_fullStr Modelo fuzzy cascata multiatributos e preditivo para despacho de AGVs em FMS
title_full_unstemmed Modelo fuzzy cascata multiatributos e preditivo para despacho de AGVs em FMS
title_sort Modelo fuzzy cascata multiatributos e preditivo para despacho de AGVs em FMS
author Caridá, Vinicius Fernandes
author_facet Caridá, Vinicius Fernandes
author_role author
dc.contributor.authorlattes.por.fl_str_mv http://lattes.cnpq.br/0843328163052788
dc.contributor.author.fl_str_mv Caridá, Vinicius Fernandes
dc.contributor.advisor1.fl_str_mv Morandin Júnior, Orides
dc.contributor.advisor1Lattes.fl_str_mv http://lattes.cnpq.br/4192845106907956
dc.contributor.authorID.fl_str_mv 76502433-7770-4536-a688-c0013d4f5960
contributor_str_mv Morandin Júnior, Orides
dc.subject.eng.fl_str_mv Fuzzy logic
Prediction
Automated Guided Vehicletems
Automated Guided Vehicle
AGV control
topic Fuzzy logic
Prediction
Automated Guided Vehicletems
Automated Guided Vehicle
AGV control
Despacho de AGVs
Inteligência artificial
Sistemas flexíveis de manufatura
CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::SISTEMAS DE COMPUTACAO
dc.subject.por.fl_str_mv Despacho de AGVs
Inteligência artificial
Sistemas flexíveis de manufatura
dc.subject.cnpq.fl_str_mv CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::SISTEMAS DE COMPUTACAO
description In recent years, manufacturers are increasingly applying automation techniques with the aim of increase their efficiency to remain competitive. The material handling is an essential activity in any process of production and its effectiveness has severe impacts on production costs. Systems of automated guided vehicles (AGVs) have become an important strategic tool for factories and automated warehouses. In a very competitive business scenario, they can increase productivity and reduce costs. The management of these AGVs is the key to a transport system that ensures the improvements envisioned by the industry. One of the main problems encountered in the management of AGVs is the dispatch decision. This paper proposes a vehicles dispatch model based on a fuzzy cascade system for consideration of multiple attributes of the factory and a structure based on state space that enables the extraction of information of future states of the industrial production system. The objective is to reduce makespan and tardiness values of the production system. Two factory scenarios are simulated and tests are performed of the model and five other methods of dispatch. A statistical validation is realized of the results in which corroborates with 97% confidence the hypotheses of the work.
publishDate 2016
dc.date.accessioned.fl_str_mv 2016-10-20T18:15:28Z
dc.date.available.fl_str_mv 2016-10-20T18:15:28Z
dc.date.issued.fl_str_mv 2016-05-02
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/doctoralThesis
format doctoralThesis
status_str publishedVersion
dc.identifier.citation.fl_str_mv CARIDÁ, Vinicius Fernandes. Modelo fuzzy cascata multiatributos e preditivo para despacho de AGVs em FMS. 2016. Tese (Doutorado em Ciência da Computação) – Universidade Federal de São Carlos, São Carlos, 2016. Disponível em: https://repositorio.ufscar.br/handle/ufscar/7985.
dc.identifier.uri.fl_str_mv https://repositorio.ufscar.br/handle/ufscar/7985
identifier_str_mv CARIDÁ, Vinicius Fernandes. Modelo fuzzy cascata multiatributos e preditivo para despacho de AGVs em FMS. 2016. Tese (Doutorado em Ciência da Computação) – Universidade Federal de São Carlos, São Carlos, 2016. Disponível em: https://repositorio.ufscar.br/handle/ufscar/7985.
url https://repositorio.ufscar.br/handle/ufscar/7985
dc.language.iso.fl_str_mv por
language por
dc.relation.confidence.fl_str_mv 600
600
dc.relation.authority.fl_str_mv 699c22db-73af-4a67-a1af-0c10448ea48b
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Universidade Federal de São Carlos
Câmpus São Carlos
dc.publisher.program.fl_str_mv Programa de Pós-Graduação em Ciência da Computação - PPGCC
dc.publisher.initials.fl_str_mv UFSCar
publisher.none.fl_str_mv Universidade Federal de São Carlos
Câmpus São Carlos
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFSCAR
instname:Universidade Federal de São Carlos (UFSCAR)
instacron:UFSCAR
instname_str Universidade Federal de São Carlos (UFSCAR)
instacron_str UFSCAR
institution UFSCAR
reponame_str Repositório Institucional da UFSCAR
collection Repositório Institucional da UFSCAR
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