Enabling Process-Aware Design Optimization for Mitigating Residual Stress and Distortion in Metal Additive Manufacturing

Wen Dong, Praveen S. Vulimiri, Albert C. To

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The MIS method can effectively predict the residual stress and distortion of metal parts manufactured by the LPBF process. Its low-cost and high-accuracy computation facilitates machine learning by providing many data samples. The ML model trained on the samples provides a good approximation of the residual stress and strain quickly for use in design optimization of the end-use application and the build process.

Original languageEnglish
Title of host publication2022 ASPE and euspen Summer Topical Meeting on Advancing Precision in Additive Manufacturing
PublisherAmerican Society for Precision Engineering, ASPE
Pages1-5
Number of pages5
ISBN (Electronic)9781713859192
StatePublished - 2022
Externally publishedYes
Event2022 ASPE and euspen Summer Topical Meeting on Advancing Precision in Additive Manufacturing - Knoxville, United States
Duration: Jul 11 2022Jul 14 2022

Publication series

Name2022 ASPE and euspen Summer Topical Meeting on Advancing Precision in Additive Manufacturing

Conference

Conference2022 ASPE and euspen Summer Topical Meeting on Advancing Precision in Additive Manufacturing
Country/TerritoryUnited States
CityKnoxville
Period07/11/2207/14/22

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