Abstract
In recent years, Finite element (FE) analysis of manufacturing using not only metal forming but also other forming processes has contributed to the improvement of these manufacturing techniques and increased knowledge regarding the deformation mechanisms that occur during forming. An analysis of spin form-ing using FE simulation was performed by authors. Moreover, a fuzzy algorithm to optimize spin forming was developed to decrease the processing time and the number of processing paths. The algorithm was validated as the processing time was shortened by around 15% less than in the case of the process without control. Furthermore, the forming velocity was increased by using the fuzzy control during the process. In this study, the fuzzy intelligent method for expanding the geometry of the blank in spin forming was investigated using the finite element method. It is shown that the flexibility of the fuzzy intelligent method investigated improves several experimental conditions and reduces the duration of the process.
| Original language | English |
|---|---|
| Pages | 719-724 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2004 Dec 1 |
| Externally published | Yes |
| Event | 2004 ASME International Mechanical Engineering Congress and Exposition, IMECE 2004 - Anaheim, CA, United States Duration: 2004 Nov 13 → 2004 Nov 19 |
Other
| Other | 2004 ASME International Mechanical Engineering Congress and Exposition, IMECE 2004 |
|---|---|
| Country | United States |
| City | Anaheim, CA |
| Period | 04/11/13 → 04/11/19 |
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ASJC Scopus subject areas
- Engineering(all)
Cite this
FE simulation of spin forming process based on fuzzy intelligent method. / Yoshihara, Shouichirou; Ray, Pinaki; MacDonald, Bryan; Koyama, Hiroshi; Kawahara, Masanori.
2004. 719-724 Paper presented at 2004 ASME International Mechanical Engineering Congress and Exposition, IMECE 2004, Anaheim, CA, United States.Research output: Contribution to conference › Paper
}
TY - CONF
T1 - FE simulation of spin forming process based on fuzzy intelligent method
AU - Yoshihara, Shouichirou
AU - Ray, Pinaki
AU - MacDonald, Bryan
AU - Koyama, Hiroshi
AU - Kawahara, Masanori
PY - 2004/12/1
Y1 - 2004/12/1
N2 - In recent years, Finite element (FE) analysis of manufacturing using not only metal forming but also other forming processes has contributed to the improvement of these manufacturing techniques and increased knowledge regarding the deformation mechanisms that occur during forming. An analysis of spin form-ing using FE simulation was performed by authors. Moreover, a fuzzy algorithm to optimize spin forming was developed to decrease the processing time and the number of processing paths. The algorithm was validated as the processing time was shortened by around 15% less than in the case of the process without control. Furthermore, the forming velocity was increased by using the fuzzy control during the process. In this study, the fuzzy intelligent method for expanding the geometry of the blank in spin forming was investigated using the finite element method. It is shown that the flexibility of the fuzzy intelligent method investigated improves several experimental conditions and reduces the duration of the process.
AB - In recent years, Finite element (FE) analysis of manufacturing using not only metal forming but also other forming processes has contributed to the improvement of these manufacturing techniques and increased knowledge regarding the deformation mechanisms that occur during forming. An analysis of spin form-ing using FE simulation was performed by authors. Moreover, a fuzzy algorithm to optimize spin forming was developed to decrease the processing time and the number of processing paths. The algorithm was validated as the processing time was shortened by around 15% less than in the case of the process without control. Furthermore, the forming velocity was increased by using the fuzzy control during the process. In this study, the fuzzy intelligent method for expanding the geometry of the blank in spin forming was investigated using the finite element method. It is shown that the flexibility of the fuzzy intelligent method investigated improves several experimental conditions and reduces the duration of the process.
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U2 - 10.1115/IMECE2004-60594
DO - 10.1115/IMECE2004-60594
M3 - Paper
SP - 719
EP - 724
ER -