Estimation of manufacturing systems degradation rate for residual life prediction through dynamic workload adjustment

Detalhes bibliográficos
Autor(a) principal: Manupati, V. K.
Data de Publicação: 2019
Outros Autores: Panigrahi, Suraj, Ahsan, Muneeb, Lahiri, Somnath, Chandra, Akshay, Thakkar, J. J., Putnik, Goran D., Varela, M.L.R.
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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spelling 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
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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)
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