Zobrazit minimální záznam

dc.contributor.authorTošenovský, Filip
dc.contributor.authorTošenovský, Josef
dc.date.accessioned2018-05-04T06:25:36Z
dc.date.available2018-05-04T06:25:36Z
dc.date.issued2017
dc.identifier.citationQuality Innovation Prosperity - Kvalita Inovácia Prosperita. 2017, vol. 21, issue 3, p. 50-61.cs
dc.identifier.issn1335-1745
dc.identifier.urihttp://hdl.handle.net/10084/126687
dc.descriptionDOI nefunkční (4.5.2018)
dc.description.abstractPurpose: The paper centres on process capability and its relation to data contamination. Process capability may be distorted due to imprecise data. The paper analyses to what extent capability changes reflect problems in data so that the changes can be attributed to data sampling rather than the true performance of the process. This is important because it is usually much simpler to increase the precision of data sampling than the process itself. Methodology/Approach: The paper has two major parts. In part one, effect of data contamination on the observed process characteristic is analysed. The effect is analysed using data obtained from simulated random drawings and the chi-squared test. In the other part, reaction of capability to data contamination is observed. The capability is measured by a univariate capability index. Findings: Regarding the sensitivity of the index to contamination, it is different depending on the capability before the contamination. This leads to conclusions about when the company using the index should focus more on the way the data is measured, and when it should focus more on improving the process in question. The analysis shows that if the company is used to high levels of capability and records its drop, it is worth analysing its measurement system first, as the index is at higher levels more sensitive to data contamination. Research Limitation/implication: The study concerns a single univariate index, and the contamination is modelled with only several probability distributions. Originality/Value of paper: The findings are not difficult to detect, but are not known in practice where companies do not realize that problems with their process capability may sometimes lie in the data they use and not in the process itself.cs
dc.format.extent149165 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoencs
dc.publisherTechnická univerzita Košicecs
dc.relation.ispartofseriesQuality Innovation Prosperity - Kvalita Inovácia Prosperitacs
dc.relation.urihttps://doi.org/10.12776/QIP.V21I3.910cs
dc.rights© 2017 by the authors. Submitted for possible open access publication 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.subjectcapability indexcs
dc.subjectdata contaminationcs
dc.subjectindex sensitivitycs
dc.titleProcess capability and data contaminationcs
dc.typearticlecs
dc.identifier.doi10.12776/QIP.V21I3.910
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume21cs
dc.description.issue3cs
dc.description.lastpage61cs
dc.description.firstpage50cs
dc.identifier.wos000429615600004


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Zobrazit minimální záznam

© 2017 by the authors. Submitted for possible open access publication under the terms and conditions of the Creative Commons Attribution (CC-BY) license.
Kromě případů, kde je uvedeno jinak, licence tohoto záznamu je © 2017 by the authors. Submitted for possible open access publication under the terms and conditions of the Creative Commons Attribution (CC-BY) license.