Estimation of manufacturing systems degradation rate for residual life prediction through dynamic workload adjustment
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/1822/62933 |
Resumo: | Complex systems in a work cell often consist of multiple units to process the manufacturing functions effectively for achieving the desired objectives. All manufacturing work cells are familiar with many unforeseeable events, for instance machine down time and scheduled maintenance. In fact, every configuration naturally exhibits some level of redundancy during those unpredictable events that may fail a small portion of units. In this work, using the remaining units and by raising the workloads on these units, up to the level of their capacities, we tried to fulfil the requirement of products. To procure the requirement, dynamic workload adjustment strategy has been suggested on two important configurations such as parallel and hybrid, by actively controlling its degradation path and failure times. During its operation, at each decision-making point, termed as decision epoch, the examination of the real-time condition monitoring data has been carried out for upgrading the posterior distribution. Using this updated distribution as the root of all operations, the residual life distribution of every concerned unit is calculated, for a particular workload. Subsequently, the establishment of an optimization scheme, i.e., an optimization framework, has been carried out with the help of the predicted residual life to eliminate the unit failures, for individual units, coinciding with each other. Eventually, with various scenarios, simulation has been carried out on the proposed methodology to assess the rate of degradation of various units. The validation of the approach's effectiveness has been shown by the simulation results on two different configurations having different scenarios. |
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Estimation of manufacturing systems degradation rate for residual life prediction through dynamic workload adjustmentResidual life predictionmulti-unit systemssimulationwork cellScience & TechnologyComplex systems in a work cell often consist of multiple units to process the manufacturing functions effectively for achieving the desired objectives. All manufacturing work cells are familiar with many unforeseeable events, for instance machine down time and scheduled maintenance. In fact, every configuration naturally exhibits some level of redundancy during those unpredictable events that may fail a small portion of units. In this work, using the remaining units and by raising the workloads on these units, up to the level of their capacities, we tried to fulfil the requirement of products. To procure the requirement, dynamic workload adjustment strategy has been suggested on two important configurations such as parallel and hybrid, by actively controlling its degradation path and failure times. During its operation, at each decision-making point, termed as decision epoch, the examination of the real-time condition monitoring data has been carried out for upgrading the posterior distribution. Using this updated distribution as the root of all operations, the residual life distribution of every concerned unit is calculated, for a particular workload. Subsequently, the establishment of an optimization scheme, i.e., an optimization framework, has been carried out with the help of the predicted residual life to eliminate the unit failures, for individual units, coinciding with each other. Eventually, with various scenarios, simulation has been carried out on the proposed methodology to assess the rate of degradation of various units. The validation of the approach's effectiveness has been shown by the simulation results on two different configurations having different scenarios.- (undefined)SpringerUniversidade do MinhoManupati, V. K.Panigrahi, SurajAhsan, MuneebLahiri, SomnathChandra, AkshayThakkar, J. J.Putnik, Goran D.Varela, M.L.R.20192019-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/62933eng0256-24990973-767710.1007/s12046-018-0991-yinfo: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:RCAAP2023-07-21T12:08:21Zoai:repositorium.sdum.uminho.pt:1822/62933Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T18:59:34.688971Repositório 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 |
Estimation of manufacturing systems degradation rate for residual life prediction through dynamic workload adjustment |
title |
Estimation of manufacturing systems degradation rate for residual life prediction through dynamic workload adjustment |
spellingShingle |
Estimation of manufacturing systems degradation rate for residual life prediction through dynamic workload adjustment Manupati, V. K. Residual life prediction multi-unit systems simulation work cell Science & Technology |
title_short |
Estimation of manufacturing systems degradation rate for residual life prediction through dynamic workload adjustment |
title_full |
Estimation of manufacturing systems degradation rate for residual life prediction through dynamic workload adjustment |
title_fullStr |
Estimation of manufacturing systems degradation rate for residual life prediction through dynamic workload adjustment |
title_full_unstemmed |
Estimation of manufacturing systems degradation rate for residual life prediction through dynamic workload adjustment |
title_sort |
Estimation of manufacturing systems degradation rate for residual life prediction through dynamic workload adjustment |
author |
Manupati, V. K. |
author_facet |
Manupati, V. K. Panigrahi, Suraj Ahsan, Muneeb Lahiri, Somnath Chandra, Akshay Thakkar, J. J. Putnik, Goran D. Varela, M.L.R. |
author_role |
author |
author2 |
Panigrahi, Suraj Ahsan, Muneeb Lahiri, Somnath Chandra, Akshay Thakkar, J. J. Putnik, Goran D. Varela, M.L.R. |
author2_role |
author author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Manupati, V. K. Panigrahi, Suraj Ahsan, Muneeb Lahiri, Somnath Chandra, Akshay Thakkar, J. J. Putnik, Goran D. Varela, M.L.R. |
dc.subject.por.fl_str_mv |
Residual life prediction multi-unit systems simulation work cell Science & Technology |
topic |
Residual life prediction multi-unit systems simulation work cell Science & Technology |
description |
Complex systems in a work cell often consist of multiple units to process the manufacturing functions effectively for achieving the desired objectives. All manufacturing work cells are familiar with many unforeseeable events, for instance machine down time and scheduled maintenance. In fact, every configuration naturally exhibits some level of redundancy during those unpredictable events that may fail a small portion of units. In this work, using the remaining units and by raising the workloads on these units, up to the level of their capacities, we tried to fulfil the requirement of products. To procure the requirement, dynamic workload adjustment strategy has been suggested on two important configurations such as parallel and hybrid, by actively controlling its degradation path and failure times. During its operation, at each decision-making point, termed as decision epoch, the examination of the real-time condition monitoring data has been carried out for upgrading the posterior distribution. Using this updated distribution as the root of all operations, the residual life distribution of every concerned unit is calculated, for a particular workload. Subsequently, the establishment of an optimization scheme, i.e., an optimization framework, has been carried out with the help of the predicted residual life to eliminate the unit failures, for individual units, coinciding with each other. Eventually, with various scenarios, simulation has been carried out on the proposed methodology to assess the rate of degradation of various units. The validation of the approach's effectiveness has been shown by the simulation results on two different configurations having different scenarios. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019 2019-01-01T00:00:00Z |
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/1822/62933 |
url |
http://hdl.handle.net/1822/62933 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
0256-2499 0973-7677 10.1007/s12046-018-0991-y |
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 |
Springer |
publisher.none.fl_str_mv |
Springer |
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 |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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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 |
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1799132387486990336 |