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Sample size analysis for a production line study of time

dc.contributor.authorSilva, Maria Isabel
dc.contributor.authorVaz, Clara B.
dc.date.accessioned2024-02-20T14:38:31Z
dc.date.available2024-02-20T14:38:31Z
dc.date.issued2024
dc.description.abstractSetting labor standards is an important topic to operational and strategic planning which requires the time studies establishment. This paper applies the statistical method for the definition of a sample size in order to define a reliable cycle time for a real industrial process. For the case study it is considered a welding process performed by a single operator that does the load and unload of components in 4 di↵erent welding machines. In order to perform the time studies, it is necessary to collect continuously data in the production line by measuring the time taken for the operator to perform the task. In order to facilitate the measurements, the task is divided into small elements with visible start and end points, called Measurement Points, in which the measurement process is applied. Afterwards, the statistical method enables to determine the sample size of observations to calculate the reliable cycle time. For the welding process presented, it is stated that the sample size defined through the statistical method is 20. Thus, these time observations of the task are continuously collected in order to obtain a reliable cycle time for this welding process. This time study can be implemented in similar way in other industrial processes.pt_PT
dc.description.sponsorshipThis work has been supported by Foundation for Science and Technology (FCT, Portugal) for financial support through national funds FCT/MCTES (PIDDAC) to CeDRI (UIDB/05757/2020 and UIDP/05757/2020) and SusTEC (LA/P/0007/2021).pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationSilva, Maria Isabel; Vaz, Clara B. (2024). Sample size analysis for a production line study of time. In 32nd International Conference on Flexible Automation and Intelligent Manufacturing (FAIM). p. 178-186. ISBN 978-3-031-38164-5pt_PT
dc.identifier.doi10.1007/978-3-031-38165-2_22pt_PT
dc.identifier.issn978-3-031-38164-5
dc.identifier.urihttp://hdl.handle.net/10198/29554
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSpringer Naturept_PT
dc.relationLA/P/0007/2021pt_PT
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.relationResearch Centre in Digitalization and Intelligent Robotics
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectStatistical analysispt_PT
dc.subjectSample sizept_PT
dc.subjectTime studiespt_PT
dc.titleSample size analysis for a production line study of timept_PT
dc.typeconference paper
dspace.entity.typePublication
oaire.awardNumberUIDB/05757/2020
oaire.awardNumberUIDP/05757/2020
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardTitleResearch Centre in Digitalization and Intelligent Robotics
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F05757%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDP%2F05757%2F2020/PT
oaire.citation.endPage186pt_PT
oaire.citation.startPage178pt_PT
oaire.citation.title32nd International Conference on Flexible Automation and Intelligent Manufacturing (FAIM)pt_PT
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
person.familyNameVaz
person.givenNameClara B.
person.identifierR-001-FQC
person.identifier.ciencia-id9611-3386-E516
person.identifier.orcid0000-0001-9862-6068
person.identifier.ridF-1519-2016
person.identifier.scopus-author-id56352045500
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsrestrictedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublication34bc350c-28d9-4b06-9874-b2b0dba58d1d
relation.isAuthorOfPublication.latestForDiscovery34bc350c-28d9-4b06-9874-b2b0dba58d1d
relation.isProjectOfPublication6e01ddc8-6a82-4131-bca6-84789fa234bd
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