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http://hdl.handle.net/10773/35460
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DC Field | Value | Language |
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dc.contributor.author | Rocha, Eugénio M. | pt_PT |
dc.contributor.author | Brochado, Ângela F. | pt_PT |
dc.contributor.author | Moura, Ana | pt_PT |
dc.date.accessioned | 2022-12-19T16:25:40Z | - |
dc.date.issued | 2022 | - |
dc.identifier.issn | 1877-0509 | pt_PT |
dc.identifier.uri | http://hdl.handle.net/10773/35460 | - |
dc.description.abstract | The human factor plays a relevant role in all manual or partially automatic production systems, specially, the ones showing reliable and balanced dynamics. In the literature, parametric or survey-based models are quite common for performance evaluation of production workers. In this work, multi-directional efficiency analysis is used instead, for root cause analysis of product reworks and bottlenecks occurrence, according to four worker-related parameters: experience time, wage, delay time and response time. The approach allows to identify individual inefficiencies per tuple worker/working shift and to cluster them according to similar inefficiency parameters. In addition, this work opens a path to new applications of multi-directional efficiency analysis to problems in the manufacturing industry. | pt_PT |
dc.language.iso | eng | pt_PT |
dc.publisher | Elsevier | pt_PT |
dc.relation | POCI-01-0247-FEDER-046103 | pt_PT |
dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04106%2F2020/PT | pt_PT |
dc.rights | openAccess | pt_PT |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | pt_PT |
dc.subject | Multi-directional efficiency analysis | pt_PT |
dc.subject | Bottleneck | pt_PT |
dc.subject | Workers performance clustering | pt_PT |
dc.subject | Manufacturing production system | pt_PT |
dc.title | Workers benchmarking using multi-directional efficiency analysis in a manufacturing production system | pt_PT |
dc.type | article | pt_PT |
dc.description.version | published | pt_PT |
dc.peerreviewed | yes | pt_PT |
degois.publication.firstPage | 1451 | pt_PT |
degois.publication.lastPage | 1460 | pt_PT |
degois.publication.title | Procedia Computer Science | pt_PT |
degois.publication.volume | 200 | pt_PT |
dc.identifier.doi | 10.1016/j.procs.2022.01.346 | pt_PT |
dc.identifier.essn | 1877-0509 | pt_PT |
Appears in Collections: | CIDMA - Artigos FAAG - Artigos |
Files in This Item:
File | Description | Size | Format | |
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1-s2.0-S1877050922003556-main.pdf | 1.3 MB | Adobe PDF | View/Open |
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