Enabling Data Analytics in Large Scale Manufacturing

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Abstract

Companies of the manufacturing industry face increasing process complexity. To remain competitive, increasing the knowledge concerning innovative manufacturing processes is necessary. In other areas, data analytics methods have been successfully applied for this purpose. Currently, their application in large scale manufacturing is hampered by insufficient data availability. Therefore, this study presents a solution approach that enables adaptive data availability by establishing a data-use-case-matrix (DUCM), which allows use case prioritization to support dimensioning of control systems and IT infrastructures. In order to support technology development, further proposed is a scalable implementation of the prioritized use cases starting in early prototyping phases.

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APA

Kampker, A., Heimes, H., Bührer, U., Lienemann, C., & Krotil, S. (2018). Enabling Data Analytics in Large Scale Manufacturing. In Procedia Manufacturing (Vol. 24, pp. 120–127). Elsevier B.V. https://doi.org/10.1016/j.promfg.2018.06.017

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