@inproceedings{3a2efbe8c96247399849df6dec7d596a,
title = "Process damping coefficient identification using Bayesian inference",
abstract = "This paper describes the application of the random walk method for Bayesian inference to the identification of the process damping coefficient in milling. An analytical process damping algorithm is used to model the prior distribution of the stability boundary and it is updated using experimental results via Bayesian inference. The updated distribution of the stability boundary is used to determine the posterior process damping coefficient value. The method is validated by comparing the process damping posterior values to residual sum of squares results. A value of information approach for experimental test point selection is demonstrated which minimizes the number of experiments required for process damping coefficient identification.",
keywords = "Bayesian inference, Milling, Process damping, Value of information",
author = "Karandikar, {Jaydeep M.} and Tyler, {Christopher T.} and Schmitz, {Tony L.}",
year = "2013",
language = "English",
isbn = "9781627486972",
series = "Transactions of the North American Manufacturing Research Institution of SME",
pages = "55--65",
booktitle = "41st North American Manufacturing Research Conference 2013 - Transactions of the North American Manufacturing Research Institution of SME, NAMRC 2013",
note = "41st North American Manufacturing Research Conference 2013, NAMRC 2013 ; Conference date: 10-06-2013 Through 14-06-2013",
}