A genetic algorithm approach to design job rotation schedules ensuring homogeneity and diversity of exposure in the automotive industry

Detalhes bibliográficos
Autor(a) principal: Assunção, Ana
Data de Publicação: 2022
Outros Autores: Mollaei, Nafiseh, Rodrigues, João, Fujão, Carlos, Osório, Daniel, Veloso, António P., Gamboa, Hugo, Carnide, Filomena
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/142752
Resumo: Publisher Copyright: © 2022 The Author(s)
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spelling A genetic algorithm approach to design job rotation schedules ensuring homogeneity and diversity of exposure in the automotive industryAutomotive industryGenetic algorithmMusculoskeletal disordersOccupational risk factorsPrevention approachWorkplace interventionGeneralPublisher Copyright: © 2022 The Author(s)Job rotation is a work organization strategy with increasing popularity, given its benefits for workers and companies, especially those working with manufacturing. This study proposes a formulation to help the team leader in an assembly line of the automotive industry to achieve job rotation schedules based on three major criteria: improve diversity, ensure homogeneity, and thus reduce exposure level. The formulation relied on a genetic algorithm, that took into consideration the biomechanical risk factors (EAWS), workers’ qualifications, and the organizational aspects of the assembly line. Moreover, the job rotation plan formulated by the genetic algorithm formulation was compared with the solution provided by the team leader in a real life-environment. The formulation proved to be a reliable solution to design job rotation plans for increasing diversity, decreasing exposure, and balancing homogeneity within workers, achieving better results in all of the outcomes when compared with the job rotation schedules created by the team leader. Additionally, this solution was less time-consuming for the team leader than a manual implementation. This study provides a much-needed solution to the job rotation issue in the manufacturing industry, with the genetic algorithm taking less time and showing better results than the job rotations created by the team leaders.LIBPhys-UNLRUNAssunção, AnaMollaei, NafisehRodrigues, JoãoFujão, CarlosOsório, DanielVeloso, António P.Gamboa, HugoCarnide, Filomena2022-08-01T22:24:33Z2022-052022-05-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article14application/pdfhttp://hdl.handle.net/10362/142752eng2405-8440PURE: 45392989https://doi.org/10.1016/j.heliyon.2022.e09396info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-05-22T18:04:10Zoai:run.unl.pt:10362/142752Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-05-22T18:04:10Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv A genetic algorithm approach to design job rotation schedules ensuring homogeneity and diversity of exposure in the automotive industry
title A genetic algorithm approach to design job rotation schedules ensuring homogeneity and diversity of exposure in the automotive industry
spellingShingle A genetic algorithm approach to design job rotation schedules ensuring homogeneity and diversity of exposure in the automotive industry
Assunção, Ana
Automotive industry
Genetic algorithm
Musculoskeletal disorders
Occupational risk factors
Prevention approach
Workplace intervention
General
title_short A genetic algorithm approach to design job rotation schedules ensuring homogeneity and diversity of exposure in the automotive industry
title_full A genetic algorithm approach to design job rotation schedules ensuring homogeneity and diversity of exposure in the automotive industry
title_fullStr A genetic algorithm approach to design job rotation schedules ensuring homogeneity and diversity of exposure in the automotive industry
title_full_unstemmed A genetic algorithm approach to design job rotation schedules ensuring homogeneity and diversity of exposure in the automotive industry
title_sort A genetic algorithm approach to design job rotation schedules ensuring homogeneity and diversity of exposure in the automotive industry
author Assunção, Ana
author_facet Assunção, Ana
Mollaei, Nafiseh
Rodrigues, João
Fujão, Carlos
Osório, Daniel
Veloso, António P.
Gamboa, Hugo
Carnide, Filomena
author_role author
author2 Mollaei, Nafiseh
Rodrigues, João
Fujão, Carlos
Osório, Daniel
Veloso, António P.
Gamboa, Hugo
Carnide, Filomena
author2_role author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv LIBPhys-UNL
RUN
dc.contributor.author.fl_str_mv Assunção, Ana
Mollaei, Nafiseh
Rodrigues, João
Fujão, Carlos
Osório, Daniel
Veloso, António P.
Gamboa, Hugo
Carnide, Filomena
dc.subject.por.fl_str_mv Automotive industry
Genetic algorithm
Musculoskeletal disorders
Occupational risk factors
Prevention approach
Workplace intervention
General
topic Automotive industry
Genetic algorithm
Musculoskeletal disorders
Occupational risk factors
Prevention approach
Workplace intervention
General
description Publisher Copyright: © 2022 The Author(s)
publishDate 2022
dc.date.none.fl_str_mv 2022-08-01T22:24:33Z
2022-05
2022-05-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/142752
url http://hdl.handle.net/10362/142752
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2405-8440
PURE: 45392989
https://doi.org/10.1016/j.heliyon.2022.e09396
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 14
application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv mluisa.alvim@gmail.com
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