Tool Life Prediction Using Bayesian Updating, M.Sc. Thesis Sharif University of Technology ; Akbari, Javad (Supervisor)
Abstract
Traditional tool life models and wear prediction do not take into account the variation inherent in metal cutting processes. These lead to additional manufacturing costs. This research presents a stochastic method for both tool life and tool wear prediction. In the first part, Bayesian inference is applied to estimate the two model constants of Taylor tool life prediction model using a discrete grid method. Tool wear tests are performed using an uncoated M42 HSS tool and AISI 1018 carbon steel work material. Test results are used to update initial beliefs about the constants and the updated beliefs are then used to predict tool life using a probability density function (pdf). Finally, the...
Cataloging briefTool Life Prediction Using Bayesian Updating, M.Sc. Thesis Sharif University of Technology ; Akbari, Javad (Supervisor)
Abstract
Traditional tool life models and wear prediction do not take into account the variation inherent in metal cutting processes. These lead to additional manufacturing costs. This research presents a stochastic method for both tool life and tool wear prediction. In the first part, Bayesian inference is applied to estimate the two model constants of Taylor tool life prediction model using a discrete grid method. Tool wear tests are performed using an uncoated M42 HSS tool and AISI 1018 carbon steel work material. Test results are used to update initial beliefs about the constants and the updated beliefs are then used to predict tool life using a probability density function (pdf). Finally, the...
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