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Simulations of Die Casting With Uncertainty Quantification

Authors
Shahane, ShantanuMujumdar, SohamKim, NamjungPriya, PikeeAluru, Narayana R.Ferreira, PlacidKapoor, Shiv G.Vanka, Surya
Issue Date
Apr-2019
Publisher
ASME
Citation
JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME, v.141, no.4
Journal Title
JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME
Volume
141
Number
4
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/82004
DOI
10.1115/1.4042583
ISSN
1087-1357
Abstract
Die casting is a type of metal casting in which a liquid metal is solidified in a reusable die. In such a complex process, measuring and controlling the process parameters are difficult. Conventional deterministic simulations are insufficient to completely estimate the effect of stochastic variation in the process parameters on product quality. In this research, a framework to simulate the effect of stochastic variation together with verification, validation, and uncertainty quantification (UQ) is proposed. This framework includes highspeed numerical simulations of solidification, microstructure, and mechanical properties prediction models along with experimental inputs for calibration and validation. Both experimental data and stochastic variation in process parameters with numerical modeling are employed, thus enhancing the utility of traditional numerical simulations used in die casting to have a better prediction of product quality. Although the framework is being developed and applied to die casting, it can be generalized to any manufacturing process or other engineering problems as well.
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Engineering (기계·스마트·산업공학부(기계공학전공))
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