Minimum cost, stability constrained preform optimization for hybrid manufacturing

Gregory Corson; Christopher Tyler; Jake Dvorak; Tony Schmitz

doi:10.1016/j.mfglet.2023.10.004

Minimum cost, stability constrained preform optimization for hybrid manufacturing

Gregory Corson, Christopher Tyler, Jake Dvorak, Tony Schmitz

Advanced Machining and Machine Tools Res

Research output: Contribution to journal › Article › peer-review

Abstract

This paper describes a new mathematical framework for optimum preform design in hybrid manufacturing, where additive manufacturing is combined with machining. The framework minimizes the combined cost for deposition and machining, while respecting the constraint imposed by machining stability (i.e., machining parameters that produce chatter are rejected). A case study is presented where a thin wall design is parameterized to describe the overbuilt deposition geometry. A grid of candidate solutions is selected to calculate cost and the stability limit considering both the part and tool dynamics. The minimum cost option is deposited and machined to demonstrate the approach.

Original language	English
Pages (from-to)	1-5
Number of pages	5
Journal	Manufacturing Letters
Volume	39
DOIs	https://doi.org/10.1016/j.mfglet.2023.10.004
State	Published - Jan 2024

Funding

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. 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 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 with the DOE Public Access Plan (https://www.energy.gov/downloads/doe-public-access-plan). The authors also acknowledge support from the NSF Engineering Research Center for Hybrid Autonomous Manufacturing Moving from Evolution to Revolution (ERC-HAMMER) under Award Number EEC-2133630. 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. 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 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 with the DOE Public Access Plan (https://www.energy.gov/downloads/doe-public-access-plan). The authors also acknowledge support from the NSF Engineering Research Center for Hybrid Autonomous Manufacturing Moving from Evolution to Revolution (ERC-HAMMER) under Award Number EEC-2133630 . 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 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 with the DOE Public Access Plan ( https://energy.gov/downloads/doe-public-access-plan ).

Keywords

Additive manufacturing
Chatter
Cost
Milling
Optimization

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10.1016/j.mfglet.2023.10.004

Cite this

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Minimum cost, stability constrained preform optimization for hybrid manufacturing

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