Virtually-guided certification with uncertainty quantification applied to die casting

Shantanu Shahane, Soham Mujumdar, Namjung Kim, Pikee Priya, Narayana R Aluru, Placid Mathew Ferreira, Shiv Gopal Kapoor, Surya Pratap Vanka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Die casting is a type of metal casting in which liquid metal is solidified in a reusable die. In such a complex process, measuring and controlling the process parameters is 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 is proposed. This framework includes high-speed numerical simulations of solidification, micro-structure 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.

Original languageEnglish (US)
Title of host publicationASME 2018 Verification and Validation Symposium, VVS 2018
PublisherAmerican Society of Mechanical Engineers (ASME)
ISBN (Electronic)9780791840795
DOIs
StatePublished - Jan 1 2018
EventASME 2018 Verification and Validation Symposium, VVS 2018 - Minneapolis, United States
Duration: May 16 2018May 18 2018

Publication series

NameASME 2018 Verification and Validation Symposium, VVS 2018

Other

OtherASME 2018 Verification and Validation Symposium, VVS 2018
CountryUnited States
CityMinneapolis
Period5/16/185/18/18

Fingerprint

Die casting
Metal casting
Computer simulation
Liquid metals
Solidification
Calibration
Mechanical properties
Microstructure
Uncertainty
Quantification
Certification
Process parameters
Numerical simulation
Metals
Product quality

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Information Systems and Management
  • Information Systems

Cite this

Shahane, S., Mujumdar, S., Kim, N., Priya, P., Aluru, N. R., Ferreira, P. M., ... Vanka, S. P. (2018). Virtually-guided certification with uncertainty quantification applied to die casting. In ASME 2018 Verification and Validation Symposium, VVS 2018 (ASME 2018 Verification and Validation Symposium, VVS 2018). American Society of Mechanical Engineers (ASME). https://doi.org/10.1115/VVS2018-9323

Virtually-guided certification with uncertainty quantification applied to die casting. / Shahane, Shantanu; Mujumdar, Soham; Kim, Namjung; Priya, Pikee; Aluru, Narayana R; Ferreira, Placid Mathew; Kapoor, Shiv Gopal; Vanka, Surya Pratap.

ASME 2018 Verification and Validation Symposium, VVS 2018. American Society of Mechanical Engineers (ASME), 2018. (ASME 2018 Verification and Validation Symposium, VVS 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Shahane, S, Mujumdar, S, Kim, N, Priya, P, Aluru, NR, Ferreira, PM, Kapoor, SG & Vanka, SP 2018, Virtually-guided certification with uncertainty quantification applied to die casting. in ASME 2018 Verification and Validation Symposium, VVS 2018. ASME 2018 Verification and Validation Symposium, VVS 2018, American Society of Mechanical Engineers (ASME), ASME 2018 Verification and Validation Symposium, VVS 2018, Minneapolis, United States, 5/16/18. https://doi.org/10.1115/VVS2018-9323
Shahane S, Mujumdar S, Kim N, Priya P, Aluru NR, Ferreira PM et al. Virtually-guided certification with uncertainty quantification applied to die casting. In ASME 2018 Verification and Validation Symposium, VVS 2018. American Society of Mechanical Engineers (ASME). 2018. (ASME 2018 Verification and Validation Symposium, VVS 2018). https://doi.org/10.1115/VVS2018-9323
Shahane, Shantanu ; Mujumdar, Soham ; Kim, Namjung ; Priya, Pikee ; Aluru, Narayana R ; Ferreira, Placid Mathew ; Kapoor, Shiv Gopal ; Vanka, Surya Pratap. / Virtually-guided certification with uncertainty quantification applied to die casting. ASME 2018 Verification and Validation Symposium, VVS 2018. American Society of Mechanical Engineers (ASME), 2018. (ASME 2018 Verification and Validation Symposium, VVS 2018).
@inproceedings{cf09d1581fed42b2a5dce8be314c0d36,
title = "Virtually-guided certification with uncertainty quantification applied to die casting",
abstract = "Die casting is a type of metal casting in which liquid metal is solidified in a reusable die. In such a complex process, measuring and controlling the process parameters is 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 is proposed. This framework includes high-speed numerical simulations of solidification, micro-structure 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.",
author = "Shantanu Shahane and Soham Mujumdar and Namjung Kim and Pikee Priya and Aluru, {Narayana R} and Ferreira, {Placid Mathew} and Kapoor, {Shiv Gopal} and Vanka, {Surya Pratap}",
year = "2018",
month = "1",
day = "1",
doi = "10.1115/VVS2018-9323",
language = "English (US)",
series = "ASME 2018 Verification and Validation Symposium, VVS 2018",
publisher = "American Society of Mechanical Engineers (ASME)",
booktitle = "ASME 2018 Verification and Validation Symposium, VVS 2018",

}

TY - GEN

T1 - Virtually-guided certification with uncertainty quantification applied to die casting

AU - Shahane, Shantanu

AU - Mujumdar, Soham

AU - Kim, Namjung

AU - Priya, Pikee

AU - Aluru, Narayana R

AU - Ferreira, Placid Mathew

AU - Kapoor, Shiv Gopal

AU - Vanka, Surya Pratap

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Die casting is a type of metal casting in which liquid metal is solidified in a reusable die. In such a complex process, measuring and controlling the process parameters is 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 is proposed. This framework includes high-speed numerical simulations of solidification, micro-structure 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.

AB - Die casting is a type of metal casting in which liquid metal is solidified in a reusable die. In such a complex process, measuring and controlling the process parameters is 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 is proposed. This framework includes high-speed numerical simulations of solidification, micro-structure 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.

UR - http://www.scopus.com/inward/record.url?scp=85050926922&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85050926922&partnerID=8YFLogxK

U2 - 10.1115/VVS2018-9323

DO - 10.1115/VVS2018-9323

M3 - Conference contribution

AN - SCOPUS:85050926922

T3 - ASME 2018 Verification and Validation Symposium, VVS 2018

BT - ASME 2018 Verification and Validation Symposium, VVS 2018

PB - American Society of Mechanical Engineers (ASME)

ER -