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.
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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
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Veröffentlicht am 10. Oktober 2019