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Production planning based on relevant data analytics

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dc.title Production planning based on relevant data analytics en
dc.contributor.author Chromjaková, Felicita
dc.contributor.author Bobák, Roman
dc.contributor.author Hrbáčková, Lucie
dc.relation.ispartof ACM International Conference Proceeding Series
dc.identifier.isbn 979-840070820-6
dc.date.issued 2023
dc.citation.spage 77
dc.citation.epage 82
dc.event.title 6th International Conference on Information Science and Systems, ICISS 2023
dc.event.location Edinburgh
utb.event.state-en United Kingdom
utb.event.state-cs Spojené království
dc.event.sdate 2023-08-11
dc.event.edate 2023-08-13
dc.type conferenceObject
dc.language.iso en
dc.publisher Association for Computing Machinery
dc.identifier.doi 10.1145/3625156.3625168
dc.relation.uri https://dl.acm.org/doi/10.1145/3625156.3625168
dc.subject data analytics en
dc.subject process en
dc.subject production en
dc.subject stability en
dc.description.abstract The presented paper is focused on the essence of data analysis-the content of production data towards the setting of reliable fixed e-data. They are the basis of effective production planning and scheduling. On the basis of theoretical research and research in selected industrial companies, we focus on the probability of abnormality in the real production plan and at the same time on the reliability of achieving the planned production output for the customer. Research questions and scientific hypotheses proved the validity of detailed data analysis of process reporting as a standardized basis for data reporting on production processes. en
utb.faculty Faculty of Management and Economics
dc.identifier.uri http://hdl.handle.net/10563/1011854
utb.identifier.obdid 43884694
utb.identifier.scopus 2-s2.0-85180154141
utb.source d-scopus
dc.date.accessioned 2024-02-14T13:51:52Z
dc.date.available 2024-02-14T13:51:52Z
dc.description.sponsorship Tomas Bata University in Zlín, TBU, (VaV/IP-RO/2022/01)
utb.ou Department of Industrial Engineering and Information Systems
utb.contributor.internalauthor Chromjaková, Felicita
utb.contributor.internalauthor Bobák, Roman
utb.contributor.internalauthor Hrbáčková, Lucie
utb.fulltext.sponsorship This research project is realized as a part of Research Grant IGA, financed by Tomas Bata University in Zlín (VaV/IP-RO/2022/01 “Predictive modelling and diagnostics of production planning and scheduling processes”.
utb.scopus.affiliation Department of Industrial Engineering and Information Systems, Faculty of Management and Economics, Tomas Bata University in Zlín, Tomas Bata University in Zlin, Mostní 5139, Zlín, 760 01, Czech Republic
utb.fulltext.projects VaV/IP-RO/2022/01
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