Bayesian stability and force modeling for uncertain machining processes

Cornelius, Aaron; Karandikar, Jaydeep; Schmitz, Tony

doi:10.1038/s44334-024-00011-y

Title: Bayesian stability and force modeling for uncertain machining processes

Journal Article · 17 December 2024 · npj Advanced Manufacturing

DOI: https://doi.org/10.1038/s44334-024-00011-y · OSTI ID:2482108

Cornelius, Aaron ^[1];

^[2]; Schmitz, Tony ^[3]

Univ. of Tennessee, Knoxville, TN (United States)
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Accurately simulating machining operations requires knowledge of the cutting force model and system frequency response. However, this data is collected using specialized instruments in an ex-situ manner. Bayesian statistical methods instead learn the system parameters using cutting test data, but to date, these approaches have only considered milling stability. This paper presents a physics-based Bayesian framework which incorporates both spindle power and milling stability. Initial probabilistic descriptions of the system parameters are propagated through a set of physics functions to form probabilistic predictions about the milling process. The system parameters are then updated using automatically selected cutting tests to reduce parameter uncertainty and identify more productive cutting conditions, where spindle power measurements are used to learn the cutting force model. The framework is demonstrated through both numerical and experimental case studies. Results show that the approach accurately identifies both the system natural frequency and cutting force model.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE

Grant/Contract Number:: AC05-00OR22725; EE0009400

OSTI ID:: 2482108

Journal Information:: npj Advanced Manufacturing, Journal Name: npj Advanced Manufacturing Journal Issue: 1 Vol. 1; ISSN 3004-8621

Publisher:: Springer NatureCopyright Statement

Country of Publication:: United States

Language:: English

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