Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/18507
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dc.contributor.authorDjordjevic, Aleksandar-
dc.contributor.authorStefanovic, Miladin-
dc.contributor.authorPetrović, Tijana-
dc.contributor.authorErić, Milan-
dc.contributor.authorKlochkov, Yury-
dc.contributor.authorMišić, Milan-
dc.date.accessioned2023-06-27T08:32:29Z-
dc.date.available2023-06-27T08:32:29Z-
dc.date.issued2023-
dc.identifier.issn0951-192Xen_US
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/18507-
dc.description.abstractThroughout industrialisation, and hence, in the Industry 4.0 era, manufacturing organisations strived to minimise nonconformities and reach zero defect manufacturing. This paper aims to propose a software solution for the detection of nonconformities and the definition of preventive and corrective actions that expands the use of edge devices in compliance with the Industry 4.0 paradigm. The software solution design presented hereafter is based on JavaScript frameworks combined in MEAN stack. The main contributions of this paper reflect in the presentation of the software solution, which allows an affordable identification and reporting of the nonconformities amidst heavy workload, integrated with other software modules for the quality analysis, problem solving, and in the comparison of the execution and subsequent performance between the established solution and prevalently used solutions based on scripting language and a relational database for a similar purpose. One-way ANOVA tests were carried out so that the performance of the considered technologies could be compared. The novelty aspects of this research are the utilization of the presented solution for real-time nonconformity categorization and the comparison to prevalently used solutions, which indicate that the proposed solution is reliable and that it performs database queries at a rate that is relatively effective.en_US
dc.language.isoenen_US
dc.relation.ispartofInternational Journal of Computer Integrated Manufacturingen_US
dc.rightsAttribution 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/us/*
dc.subjectQuality 4.0en_US
dc.subjectnonconformity reporten_US
dc.subjectnonconformity managementen_US
dc.subjectopen-source solutionen_US
dc.titleJavaScript MEAN stack application approach for real-time nonconformity management in SMEs as a quality control aspect within Industry 4.0 concepten_US
dc.typearticleen_US
dc.description.versionPublisheden_US
dc.identifier.doi10.1080/0951192X.2023.2228274en_US
dc.type.versionPublishedVersionen_US
Appears in Collections:Faculty of Engineering, Kragujevac

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