Propagation of Johnson-Cook flow stress model uncertainty to milling force uncertainty using finite element analysis and time domain simulation

Timothy No; Michael Gomez; Jaydeep Karandikar; Jarred Heigel; Ryan Copenhaver; Tony Schmitz

doi:10.1016/j.promfg.2021.06.025

Propagation of Johnson-Cook flow stress model uncertainty to milling force uncertainty using finite element analysis and time domain simulation

Timothy No, Michael Gomez, Jaydeep Karandikar, Jarred Heigel, Ryan Copenhaver, Tony Schmitz

Advanced Machining and Machine Tools Res

Research output: Contribution to journal › Conference article › peer-review

6 Scopus citations

Abstract

This paper describes the propagation of uncertainty in the parameters for a 6061-T6 aluminum Johnson-Cook flow stress model to, first, the uncertainty in the corresponding mechanistic cutting force model obtained by orthogonal cutting finite element simulation and, second, the milling force predicted by time domain simulation using the force model. The approach includes five key elements: 1) a literature review to identify the means and standard deviations for the 6061-T6 aluminum Johnson-Cook model parameters; 2) structured light scanning to measure an endmill's cutting edge macro-geometry along the tool axis; 3) structured light scanning to identify the cutting edge cross-sectional rake and relief profiles for the same endmill; 4) orthogonal cutting finite element analysis to determine the mechanistic force model coefficients that relate the force components to chip area and width using the tool's rake and relief profiles and random samples from the Johnson-Cook parameter distributions; and 5) time domain simulation with inputs that include the measured cutting edge macro-geometry, uncertain finite element-based force model, and measured structural dynamics. Distributions for milling force predictions are determined by Monte Carlo simulation and compared to in-process measurements for an indexable endmill-collet holder to demonstrate the approach. It is observed that 95% confidence intervals on the predicted forces bound the measured time-dependent force profile peaks in over half of the cases tested. It is also seen that the Johnson-Cook flow stress model-based force predictions performed as well as predictions based on a calibrated mechanistic force model.

Original language	English
Pages (from-to)	223-235
Number of pages	13
Journal	Procedia Manufacturing
Volume	53
DOIs	https://doi.org/10.1016/j.promfg.2021.06.025
State	Published - 2021
Event	49th SME North American Manufacturing Research Conference, NAMRC 2021 - Cincinnati, United States Duration: Jun 21 2021 → Jun 25 2021

Funding

The authors gratefully acknowledge financial support from the National Science Foundation (CMMI-1561221). Additionally, this research was supported by the DOE Office of Energy Efficiency and Renewable Energy (EERE), Energy and Transportation Science Division and used resources at the Manufacturing Demonstration Facility, a DOE-EERE User Facility at Oak Ridge National Laboratory. *publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the *published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance Notice: This manuscript has been authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the pubwithlitshheerDO, fboyErmaPcocuebfplithtciinsAgmctchaeensuassrPctirlciaplnet,(fhororttpapl:ul//obewlneicoarttgyhioe.nrgos, atvoc/dow kdnoo wsnloadsol,efdogreUs/doetSh ag-to putvheblernUicmS-accese gnot vpeusrr-nppmolasenen)st.. rDetOaiEnswailnlopnroevxcidlues pivueb,lipca aidc-cueps,sitroretvhoecsea brlees,uwltsoroldfwfeiddeeralilclyensspeotnos opruebdlirsehseoarrrcehpirnodauccceortdhaence publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the witpuibthhlittshheedDOD fOoEErmPPouubbfliltihccisAAmccccaeenssusssPPcrlliaapnnt,((hhotttrtppal::l///o/eewneneorrtgyghye..rgogsotvvo/dow/ ddoow snloadsnol,ofaodrsU/doe/dSo eg--opupvueblbrlniiccm--accesaecnct epsussr--ppolalasnne))s.. DOE will provide public access to these results of federally sponsored research in accordance published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

Funders	Funder number
DOE-EERE
National Science Foundation	CMMI-1561221
National Science Foundation
U.S. Department of Energy
Office of Energy Efficiency and Renewable Energy
Oak Ridge National Laboratory

Keywords

Finite element analysis
Force
Johnson-Cook
Milling
Modeling
Structured light
Uncertainty

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10.1016/j.promfg.2021.06.025

Cite this

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title = "Propagation of Johnson-Cook flow stress model uncertainty to milling force uncertainty using finite element analysis and time domain simulation",

abstract = "This paper describes the propagation of uncertainty in the parameters for a 6061-T6 aluminum Johnson-Cook flow stress model to, first, the uncertainty in the corresponding mechanistic cutting force model obtained by orthogonal cutting finite element simulation and, second, the milling force predicted by time domain simulation using the force model. The approach includes five key elements: 1) a literature review to identify the means and standard deviations for the 6061-T6 aluminum Johnson-Cook model parameters; 2) structured light scanning to measure an endmill's cutting edge macro-geometry along the tool axis; 3) structured light scanning to identify the cutting edge cross-sectional rake and relief profiles for the same endmill; 4) orthogonal cutting finite element analysis to determine the mechanistic force model coefficients that relate the force components to chip area and width using the tool's rake and relief profiles and random samples from the Johnson-Cook parameter distributions; and 5) time domain simulation with inputs that include the measured cutting edge macro-geometry, uncertain finite element-based force model, and measured structural dynamics. Distributions for milling force predictions are determined by Monte Carlo simulation and compared to in-process measurements for an indexable endmill-collet holder to demonstrate the approach. It is observed that 95% confidence intervals on the predicted forces bound the measured time-dependent force profile peaks in over half of the cases tested. It is also seen that the Johnson-Cook flow stress model-based force predictions performed as well as predictions based on a calibrated mechanistic force model.",

keywords = "Finite element analysis, Force, Johnson-Cook, Milling, Modeling, Structured light, Uncertainty",

author = "Timothy No and Michael Gomez and Jaydeep Karandikar and Jarred Heigel and Ryan Copenhaver and Tony Schmitz",

note = "Publisher Copyright: {\textcopyright} 2021 The Authors. Published by Elsevier B.V.; 49th SME North American Manufacturing Research Conference, NAMRC 2021 ; Conference date: 21-06-2021 Through 25-06-2021",

year = "2021",

doi = "10.1016/j.promfg.2021.06.025",

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T1 - Propagation of Johnson-Cook flow stress model uncertainty to milling force uncertainty using finite element analysis and time domain simulation

AU - No, Timothy

AU - Gomez, Michael

AU - Karandikar, Jaydeep

AU - Heigel, Jarred

AU - Copenhaver, Ryan

AU - Schmitz, Tony

PY - 2021

Y1 - 2021

N2 - This paper describes the propagation of uncertainty in the parameters for a 6061-T6 aluminum Johnson-Cook flow stress model to, first, the uncertainty in the corresponding mechanistic cutting force model obtained by orthogonal cutting finite element simulation and, second, the milling force predicted by time domain simulation using the force model. The approach includes five key elements: 1) a literature review to identify the means and standard deviations for the 6061-T6 aluminum Johnson-Cook model parameters; 2) structured light scanning to measure an endmill's cutting edge macro-geometry along the tool axis; 3) structured light scanning to identify the cutting edge cross-sectional rake and relief profiles for the same endmill; 4) orthogonal cutting finite element analysis to determine the mechanistic force model coefficients that relate the force components to chip area and width using the tool's rake and relief profiles and random samples from the Johnson-Cook parameter distributions; and 5) time domain simulation with inputs that include the measured cutting edge macro-geometry, uncertain finite element-based force model, and measured structural dynamics. Distributions for milling force predictions are determined by Monte Carlo simulation and compared to in-process measurements for an indexable endmill-collet holder to demonstrate the approach. It is observed that 95% confidence intervals on the predicted forces bound the measured time-dependent force profile peaks in over half of the cases tested. It is also seen that the Johnson-Cook flow stress model-based force predictions performed as well as predictions based on a calibrated mechanistic force model.

AB - This paper describes the propagation of uncertainty in the parameters for a 6061-T6 aluminum Johnson-Cook flow stress model to, first, the uncertainty in the corresponding mechanistic cutting force model obtained by orthogonal cutting finite element simulation and, second, the milling force predicted by time domain simulation using the force model. The approach includes five key elements: 1) a literature review to identify the means and standard deviations for the 6061-T6 aluminum Johnson-Cook model parameters; 2) structured light scanning to measure an endmill's cutting edge macro-geometry along the tool axis; 3) structured light scanning to identify the cutting edge cross-sectional rake and relief profiles for the same endmill; 4) orthogonal cutting finite element analysis to determine the mechanistic force model coefficients that relate the force components to chip area and width using the tool's rake and relief profiles and random samples from the Johnson-Cook parameter distributions; and 5) time domain simulation with inputs that include the measured cutting edge macro-geometry, uncertain finite element-based force model, and measured structural dynamics. Distributions for milling force predictions are determined by Monte Carlo simulation and compared to in-process measurements for an indexable endmill-collet holder to demonstrate the approach. It is observed that 95% confidence intervals on the predicted forces bound the measured time-dependent force profile peaks in over half of the cases tested. It is also seen that the Johnson-Cook flow stress model-based force predictions performed as well as predictions based on a calibrated mechanistic force model.

KW - Finite element analysis

KW - Force

KW - Johnson-Cook

KW - Milling

KW - Modeling

KW - Structured light

KW - Uncertainty

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JO - Procedia Manufacturing

JF - Procedia Manufacturing

T2 - 49th SME North American Manufacturing Research Conference, NAMRC 2021

Y2 - 21 June 2021 through 25 June 2021

ER -

Propagation of Johnson-Cook flow stress model uncertainty to milling force uncertainty using finite element analysis and time domain simulation

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