The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 31, 2024

Filed:

Nov. 18, 2021
Applicant:

Ut-battelle, Llc, Oak Ridge, TN (US);

Inventors:

Jaydeep M. Karandikar, Oak Ridge, TN (US);

Thomas A. Feldhausen, Oak Ridge, TN (US);

Kyle S. Saleeby, Oak Ridge, TN (US);

Kevin S. Smith, Oak Ridge, TN (US);

Tony L. Schmitz, Oak Ridge, TN (US);

Assignee:

UT-Battelle, LLC, Oak Ridge, TN (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G05B 19/18 (2006.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G05B 19/18 (2013.01); G06N 20/00 (2019.01);
Abstract

A Bayesian learning approach for stability boundary and optimal parameter identification in milling without the knowledge of the underlying tool dynamics or material cutting force coefficients. Different axial depth and spindle speed combinations are characterized by a probability of stability which is updated based upon whether the result is stable or unstable. A likelihood function incorporates knowledge of stability behavior. Numerical results show convergence to an analytical stability lobe diagram. An adaptive experimental strategy identifies optimal operating parameters that maximize material removal rate. An efficient and robust learning method to identify the stability lobe diagram and optimal operating parameters with a limited number of tests/data points.


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