Zobrazit minimální záznam

dc.contributor.authorSmajdorová, Tereza
dc.contributor.authorNoskievičová, Darja
dc.date.accessioned2022-09-07T07:09:24Z
dc.date.available2022-09-07T07:09:24Z
dc.date.issued2022
dc.identifier.citationApplied Sciences. 2022, vol. 12, issue 11, art. no. 5410.cs
dc.identifier.issn2076-3417
dc.identifier.urihttp://hdl.handle.net/10084/148589
dc.description.abstractNonparametric control charts (NPCC) have shown great potential for monitoring processes in conditions of smart manufacturing with complex structures, various monitored characteristics and the need to process big data. Practical applications of NPCCs are very rare. The main reasons for this situation are a deficiency in software support and a lack of simple but complete instructions for their application. The introduction of such manual, which is based on the authors' own simulations of performance of wide spectrum of NPCCs in conditions of different violations of data prerequisites, leading to recommendations for the selection of the most effective NPCC in various practical situations, is the main goal of this paper. Compared to other similar studies, this approach covers a wider range of control charts, and it was applied to a wider spectrum of data assumption violations. As an integral part of these analyses, an examination of various control chart performance indicators such as ARL, MRL, x(5) and x(95) was performed using simulations to select the best of them. The designed methodology was verified using real data.cs
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofseriesApplied Sciencescs
dc.relation.urihttps://doi.org/10.3390/app12115410cs
dc.rights© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectnonparametric control chartscs
dc.subjectcontrol chart performance simulationscs
dc.subjectcontrol chart performance indicatorscs
dc.subjectdata assumption violationscs
dc.subjectsmart manufacturingcs
dc.titleAnalysis and application of selected control charts suitable for smart manufacturing processescs
dc.typearticlecs
dc.identifier.doi10.3390/app12115410
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume12cs
dc.description.issue11cs
dc.description.firstpageart. no. 5410cs
dc.identifier.wos000808797400001


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Zobrazit minimální záznam

© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.
Kromě případů, kde je uvedeno jinak, licence tohoto záznamu je © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license.