Abstract
Due to the high cost of metal forming tools (especially in hot extrusion), one of the major goals in tool design is a longer service life. Estimation and prediction of tool life thus becomes critically important for performance evaluation of the tools. The two most dominant failure mechanisms for extrusion dies (solid, hollow, and semi-hollow dies all taken together) are fracture and wear. In the first part of the paper, a fracture mechanics based fatigue life prediction model is described. A similar treatment is then presented for wear-related failures. Fracture and wear usually coexist as failure modes, and final die breakdown occurs due to the mechanism that becomes dominant. Therefore, a competing fracture-wear model has been later developed to represent the complete die failure situation. Attempt has been made to correlate the stochastic nature of various fatigue and wear related die parameters to die life. Monte Carlo simulation has been used to predict the life distribution of a die for a given set of manufacturing conditions and mechanical properties. In comparison with actual life data from the industry, the simulated life yields very realistic predictions.
| Original language | English |
|---|---|
| Pages (from-to) | 96-106 |
| Number of pages | 11 |
| Journal | Journal of Materials Processing Technology |
| Volume | 202 |
| Issue number | 1-3 |
| DOIs | |
| Publication status | Published - Jun 20 2008 |
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Keywords
- Aluminum extrusion
- Die failure
- Die life
- Fatigue fracture
- Monte Carlo simulation
- Wear
ASJC Scopus subject areas
- Materials Science(all)
Cite this
Monte Carlo simulation of extrusion die life. / Qamar, S. Z.; Sheikh, A. K.; Arif, A. F M; Younas, M.; Pervez, T.
In: Journal of Materials Processing Technology, Vol. 202, No. 1-3, 20.06.2008, p. 96-106.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Monte Carlo simulation of extrusion die life
AU - Qamar, S. Z.
AU - Sheikh, A. K.
AU - Arif, A. F M
AU - Younas, M.
AU - Pervez, T.
PY - 2008/6/20
Y1 - 2008/6/20
N2 - Due to the high cost of metal forming tools (especially in hot extrusion), one of the major goals in tool design is a longer service life. Estimation and prediction of tool life thus becomes critically important for performance evaluation of the tools. The two most dominant failure mechanisms for extrusion dies (solid, hollow, and semi-hollow dies all taken together) are fracture and wear. In the first part of the paper, a fracture mechanics based fatigue life prediction model is described. A similar treatment is then presented for wear-related failures. Fracture and wear usually coexist as failure modes, and final die breakdown occurs due to the mechanism that becomes dominant. Therefore, a competing fracture-wear model has been later developed to represent the complete die failure situation. Attempt has been made to correlate the stochastic nature of various fatigue and wear related die parameters to die life. Monte Carlo simulation has been used to predict the life distribution of a die for a given set of manufacturing conditions and mechanical properties. In comparison with actual life data from the industry, the simulated life yields very realistic predictions.
AB - Due to the high cost of metal forming tools (especially in hot extrusion), one of the major goals in tool design is a longer service life. Estimation and prediction of tool life thus becomes critically important for performance evaluation of the tools. The two most dominant failure mechanisms for extrusion dies (solid, hollow, and semi-hollow dies all taken together) are fracture and wear. In the first part of the paper, a fracture mechanics based fatigue life prediction model is described. A similar treatment is then presented for wear-related failures. Fracture and wear usually coexist as failure modes, and final die breakdown occurs due to the mechanism that becomes dominant. Therefore, a competing fracture-wear model has been later developed to represent the complete die failure situation. Attempt has been made to correlate the stochastic nature of various fatigue and wear related die parameters to die life. Monte Carlo simulation has been used to predict the life distribution of a die for a given set of manufacturing conditions and mechanical properties. In comparison with actual life data from the industry, the simulated life yields very realistic predictions.
KW - Aluminum extrusion
KW - Die failure
KW - Die life
KW - Fatigue fracture
KW - Monte Carlo simulation
KW - Wear
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UR - http://www.scopus.com/inward/citedby.url?scp=43049106182&partnerID=8YFLogxK
U2 - 10.1016/j.jmatprotec.2007.08.062
DO - 10.1016/j.jmatprotec.2007.08.062
M3 - Article
AN - SCOPUS:43049106182
VL - 202
SP - 96
EP - 106
JO - Journal of Materials Processing Technology
JF - Journal of Materials Processing Technology
SN - 0924-0136
IS - 1-3
ER -