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.
