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  • Bayesian-Based Predictive Analytics for Manufacturing Performance Metrics in the Era of Industry 4.0

    Mehdi Salehi

    Band 2019,2 von Reihe Informationsmanagement im Engineering Karlsruhe
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    The research in this dissertation proposes Bayesian-based predictive analytics for modeling and prediction of the manufacturing metrics such as cutting force, tool life and reliability in the technological era of Industry 4.0. Bayesian statistics is a probabilistic method, which can quantify and minimize manufacturing process uncertainties. The Bayesian method combines previous knowledge about the manufacturing models with experimental data to predict the manufacturing metrics.

    Umfang: XVI, 176 S.

    Preis: €47.00 | £43.00 | $83.00

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    Empfohlene Zitierweise
    Salehi, M. 2019. Bayesian-Based Predictive Analytics for Manufacturing Performance Metrics in the Era of Industry 4.0. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000091806
    Salehi, M., 2019. Bayesian-Based Predictive Analytics for Manufacturing Performance Metrics in the Era of Industry 4.0. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000091806
    Salehi, M. Bayesian-based Predictive Analytics for Manufacturing Performance Metrics in the Era of Industry 4.0. KIT Scientific Publishing, 2019. DOI: https://doi.org/10.5445/KSP/1000091806
    Salehi, M. (2019). Bayesian-Based Predictive Analytics for Manufacturing Performance Metrics in the Era of Industry 4.0. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000091806
    Salehi, Mehdi. 2019. Bayesian-based Predictive Analytics for Manufacturing Performance Metrics in the Era of Industry 4.0. Karlsruhe: KIT Scientific Publishing. DOI: https://doi.org/10.5445/KSP/1000091806




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    Weitere Informationen

    Veröffentlicht am 10. Oktober 2019

    Sprache

    Englisch

    Seitenanzahl:

    220

    ISBN
    Paperback 978-3-7315-0908-0

    DOI
    https://doi.org/10.5445/KSP/1000091806