Abstract
As a consequence of the fourth industrial revolution, the data produced by companies’ day-by-day activities and the rate at which the transactions occur are growing exponentially. In order to extract business value from those data, they need to be organised under a reference conceptual model facilitating data analysis and decision making. Since no sound reference model for organising digital factory production data has been proposed in the literature, this paper aims at developing and testing a conceptual multidimensional model to support a broad range of data analytics activities for the management and optimisation of production in a smart factory. The testing of the model in a case study company of the printing sector provides insights into the applicability of the model and the connected benefits.
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This work was supported by Regione Lombardia (POR FESR 2014–2020), under Grant 236789.
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Boniotti, G., Cocca, P., Marciano, F., Marini, A., Stefana, E., Vernuccio, F. (2021). A Conceptual Reference Model for Smart Factory Production Data. In: Dolgui, A., Bernard, A., Lemoine, D., von Cieminski, G., Romero, D. (eds) Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems. APMS 2021. IFIP Advances in Information and Communication Technology, vol 633. Springer, Cham. https://doi.org/10.1007/978-3-030-85910-7_12
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DOI: https://doi.org/10.1007/978-3-030-85910-7_12
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