Lean manufacturing and ergonomics integration: defining productivity and wellbeing indicators in a human–robot workstation
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Texto Completo: | http://hdl.handle.net/1822/72450 |
Resumo: | Lean Manufacturing (LM), Ergonomics and Human Factors (E&HF), and Human–Robot Collaboration (HRC) are vibrant topics for researchers and companies. Among other emergent technologies, collaborative robotics is an innovative solution to reduce ergonomic concerns and improve manufacturing productivity. However, there is a lack of studies providing empirical evidence about the implementation of these technologies, with little or no consideration for E&HF. This study analyzes an industrial implementation of a collaborative robotic workstation for assembly tasks performed by workers with musculoskeletal complaints through a synergistic integration of E&HF and LM principles. We assessed the workstation before and after the implementation of robotic technology and measured different key performance indicators (e.g., production rate) through a time study and direct observation. We considered 40 postures adopted during the assembly tasks and applied three assessment methods: Rapid Upper Limb Assessment, Revised Strain Index, and Key Indicator Method. Furthermore, we conducted a questionnaire to collect more indicators of workers’ wellbeing. This multi-method approach demonstrated that the hybrid workstation achieved: (i) a reduction of production times; (ii) an improvement of ergonomic conditions; and (iii) an enhancement of workers’ wellbeing. This ergonomic lean study based on human-centered principles proved to be a valid and efficient method to implement and assess collaborative workstations, foreseeing the continuous improvement of the involved processes. |
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Lean manufacturing and ergonomics integration: defining productivity and wellbeing indicators in a human–robot workstationErgonomics and human factorsLean manufacturingCollaborative roboticsProductivityMusculoskeletal riskScience & TechnologyLean Manufacturing (LM), Ergonomics and Human Factors (E&HF), and Human–Robot Collaboration (HRC) are vibrant topics for researchers and companies. Among other emergent technologies, collaborative robotics is an innovative solution to reduce ergonomic concerns and improve manufacturing productivity. However, there is a lack of studies providing empirical evidence about the implementation of these technologies, with little or no consideration for E&HF. This study analyzes an industrial implementation of a collaborative robotic workstation for assembly tasks performed by workers with musculoskeletal complaints through a synergistic integration of E&HF and LM principles. We assessed the workstation before and after the implementation of robotic technology and measured different key performance indicators (e.g., production rate) through a time study and direct observation. We considered 40 postures adopted during the assembly tasks and applied three assessment methods: Rapid Upper Limb Assessment, Revised Strain Index, and Key Indicator Method. Furthermore, we conducted a questionnaire to collect more indicators of workers’ wellbeing. This multi-method approach demonstrated that the hybrid workstation achieved: (i) a reduction of production times; (ii) an improvement of ergonomic conditions; and (iii) an enhancement of workers’ wellbeing. This ergonomic lean study based on human-centered principles proved to be a valid and efficient method to implement and assess collaborative workstations, foreseeing the continuous improvement of the involved processes.This work has been supported by NORTE-06-3559-FSE-000018; integrated in the invitation NORTE-59-2018-41, aiming at the Hiring of Highly Qualified Human Resources, co-financed by the Regional Operational Programme of the North 2020, thematic area of Competitiveness and Employment, through the European Social Fund (ESF). This work has been also supported by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020.Multidisciplinary Digital Publishing Institute (MDPI)Universidade do MinhoColim, AnaMorgado, RitaCarneiro, P.Costa, Nélson Bruno Martins Marques daFaria, CarlosSousa, Nuno Miguel AlvesRocha, Luís A.Arezes, P.2021-02-112021-02-11T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/72450eng2071-105010.3390/su13041931https://www.mdpi.com/2071-1050/13/4/1931info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T05:48:36Zoai:repositorium.sdum.uminho.pt:1822/72450Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T15:30:43.627602Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse |
dc.title.none.fl_str_mv |
Lean manufacturing and ergonomics integration: defining productivity and wellbeing indicators in a human–robot workstation |
title |
Lean manufacturing and ergonomics integration: defining productivity and wellbeing indicators in a human–robot workstation |
spellingShingle |
Lean manufacturing and ergonomics integration: defining productivity and wellbeing indicators in a human–robot workstation Colim, Ana Ergonomics and human factors Lean manufacturing Collaborative robotics Productivity Musculoskeletal risk Science & Technology |
title_short |
Lean manufacturing and ergonomics integration: defining productivity and wellbeing indicators in a human–robot workstation |
title_full |
Lean manufacturing and ergonomics integration: defining productivity and wellbeing indicators in a human–robot workstation |
title_fullStr |
Lean manufacturing and ergonomics integration: defining productivity and wellbeing indicators in a human–robot workstation |
title_full_unstemmed |
Lean manufacturing and ergonomics integration: defining productivity and wellbeing indicators in a human–robot workstation |
title_sort |
Lean manufacturing and ergonomics integration: defining productivity and wellbeing indicators in a human–robot workstation |
author |
Colim, Ana |
author_facet |
Colim, Ana Morgado, Rita Carneiro, P. Costa, Nélson Bruno Martins Marques da Faria, Carlos Sousa, Nuno Miguel Alves Rocha, Luís A. Arezes, P. |
author_role |
author |
author2 |
Morgado, Rita Carneiro, P. Costa, Nélson Bruno Martins Marques da Faria, Carlos Sousa, Nuno Miguel Alves Rocha, Luís A. Arezes, P. |
author2_role |
author author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Colim, Ana Morgado, Rita Carneiro, P. Costa, Nélson Bruno Martins Marques da Faria, Carlos Sousa, Nuno Miguel Alves Rocha, Luís A. Arezes, P. |
dc.subject.por.fl_str_mv |
Ergonomics and human factors Lean manufacturing Collaborative robotics Productivity Musculoskeletal risk Science & Technology |
topic |
Ergonomics and human factors Lean manufacturing Collaborative robotics Productivity Musculoskeletal risk Science & Technology |
description |
Lean Manufacturing (LM), Ergonomics and Human Factors (E&HF), and Human–Robot Collaboration (HRC) are vibrant topics for researchers and companies. Among other emergent technologies, collaborative robotics is an innovative solution to reduce ergonomic concerns and improve manufacturing productivity. However, there is a lack of studies providing empirical evidence about the implementation of these technologies, with little or no consideration for E&HF. This study analyzes an industrial implementation of a collaborative robotic workstation for assembly tasks performed by workers with musculoskeletal complaints through a synergistic integration of E&HF and LM principles. We assessed the workstation before and after the implementation of robotic technology and measured different key performance indicators (e.g., production rate) through a time study and direct observation. We considered 40 postures adopted during the assembly tasks and applied three assessment methods: Rapid Upper Limb Assessment, Revised Strain Index, and Key Indicator Method. Furthermore, we conducted a questionnaire to collect more indicators of workers’ wellbeing. This multi-method approach demonstrated that the hybrid workstation achieved: (i) a reduction of production times; (ii) an improvement of ergonomic conditions; and (iii) an enhancement of workers’ wellbeing. This ergonomic lean study based on human-centered principles proved to be a valid and efficient method to implement and assess collaborative workstations, foreseeing the continuous improvement of the involved processes. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-02-11 2021-02-11T00:00:00Z |
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/1822/72450 |
url |
http://hdl.handle.net/1822/72450 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2071-1050 10.3390/su13041931 https://www.mdpi.com/2071-1050/13/4/1931 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Multidisciplinary Digital Publishing Institute (MDPI) |
publisher.none.fl_str_mv |
Multidisciplinary Digital Publishing Institute (MDPI) |
dc.source.none.fl_str_mv |
reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia instacron:RCAAP |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
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Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
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