Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/122607
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dc.contributor.authorKról, Krzysztof-
dc.contributor.authorKaleta, Paweł-
dc.contributor.authorKasperek, Dariusz-
dc.contributor.authorSkrzypek-Ahmed, Sylwia-
dc.contributor.authorJózefacki, Emanuel-
dc.contributor.authorChmielowska-Marmucka, Agnieszka-
dc.date.accessioned2024-05-22T08:05:47Z-
dc.date.available2024-05-22T08:05:47Z-
dc.date.issued2024-
dc.identifier.citationKról, K., Kaleta, P., Kasperek, D., Skrzypek-Ahmed, S., Józefacki, E., & Chmielowska-Marmucka, A. (2024). Analysis system for logistics and production processes : a methodological approach to signal analysis for forecasting. European Research Studies Journal, 27(s2), 59-71.en_GB
dc.identifier.urihttps://www.um.edu.mt/library/oar/handle/123456789/122607-
dc.description.abstractPURPOSE: The article aims to present elements for analysis systems in industrial and logistics processes.en_GB
dc.description.abstractDESIGN/METHODOLOGY/APPROACH: The article presents the preparation of a module for the analysis of production processes and support for logistics processes. The use of time series, randomness test, and correlation test is presented—a comparison of measurement results from various sensors used in industry and transport.en_GB
dc.description.abstractFINDINGS: The study's result was the analysis of waveforms from sensors for controlling the operating parameters of production and logistics systems. Preparing such a forecast solution allows you to check many possible measurement process results and support decisions in the system's operation, allowing for better decision-making in conditions of uncertainty.en_GB
dc.description.abstractPRACTICAL IMPLICATIONS: The presented method of signal analysis for forecasting the system's behavior and operation can support decision-makers in taking appropriate actions, and in the future, it will allow the system to manage itself automatically.en_GB
dc.description.abstractORIGINALITY/VALUE: A new feature uses time series, randomness, and correlation tests to review and monitor the performance of various types of sensors in logistics and production systems.en_GB
dc.language.isoenen_GB
dc.publisherUniversity of Piraeus. International Strategic Management Associationen_GB
dc.rightsinfo:eu-repo/semantics/openAccessen_GB
dc.subjectTime-series analysisen_GB
dc.subjectBusiness logisticsen_GB
dc.subjectCorrelation (Statistics)en_GB
dc.subjectProcess controlen_GB
dc.titleAnalysis system for logistics and production processes : a methodological approach to signal analysis for forecastingen_GB
dc.typearticleen_GB
dc.rights.holderThe copyright of this work belongs to the author(s)/publisher. The rights of this work are as defined by the appropriate Copyright Legislation or as modified by any successive legislation. Users may access this work and can make use of the information contained in accordance with the Copyright Legislation provided that the author must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the prior permission of the copyright holder.en_GB
dc.description.reviewedpeer-revieweden_GB
dc.identifier.doi10.35808/ersj/3387-
dc.publication.titleEuropean Research Studies Journalen_GB
Appears in Collections:European Research Studies Journal, Volume 27, Special Issue 2

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