Abstract
The EMuDig 4.0 project target is to link all relevant systems and sensors inside a massive forming company with influencing systems from outside as basis for a smart factory. Data and information extracted from integrated sensors and systems in connection with new methods for analysis and algorithms shall be used to optimize the OEE of massive forming machines. The primary target is a quick and direct information to indicate machine irregularities as soon as they appear. The available information not only allows efficiency improvement of single process steps. It supports the optimization of the whole value-added chain.
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Stüer P (2015) RWTH Publications, [Online] Available at: https://publications.rwth-aachen.de/record/465189?ln=de [Haettu 15 05 2017]
SMS group GmbH (2016) Düsseldorf: SMS group GmbH
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Ecker, M., Hellfeier, M. (2019). Forecast Model for Optimization of the Massive Forming Machine OEE. In: Mathew, J., Lim, C., Ma, L., Sands, D., Cholette, M., Borghesani, P. (eds) Asset Intelligence through Integration and Interoperability and Contemporary Vibration Engineering Technologies. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-95711-1_15
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DOI: https://doi.org/10.1007/978-3-319-95711-1_15
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