Development of Intelligent Incremental Forming Machine and Its Application to Metal-Flow Controlling of Sheet Metal Stretching
| Project/Area Number |
09650134
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
機械工作・生産工学
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| Research Institution | Shinshu University |
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Principal Investigator |
KITAZAWA Kimiyoshi Shinshu University, Faculty of Eng., Associate Prof., 工学部, 助教授 (90143825)
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| Project Period (FY) |
1997 – 1998
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| Project Status |
Completed (Fiscal Year 1998)
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| Budget Amount *help |
¥3,900,000 (Direct Cost: ¥3,900,000)
Fiscal Year 1998: ¥500,000 (Direct Cost: ¥500,000)
Fiscal Year 1997: ¥3,400,000 (Direct Cost: ¥3,400,000)
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| Keywords | Intelligent Incremental forming / Sheet metal forming / Stretching / Laser / Small-lot production / Tool-path schedule / Metal-flow control / Precision forming / 知能インクリメンタル成形 / 塑性加工 / 板材成形 / インクリメンタルフォーミング / CNC塑性加工機 / CAF / 知能化メタルフロー制御 / レーザー計測 / 触覚 |
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| Research Abstract |
An incremental forming is a process in which a sheet metal is stretched to fit on a tool-envelope surface made by relative motion of a tool around the sheet metal. The incremental forming process seems to be suited to small-lot production from viewpoint of a die-less forming operation, and is also thought to be important in metal-flow control operation. Although the incremental forming posses large degrees of freedom of tool motion, an algorithm for estimating automatically an adequate tool-path schedule has not been illuminated. So as to overcome the need for estimating the adequate tool-path schedules, this study presents the development of an intelligent incremental forming machine and the proposal of an algorithm for deducing the tool-path schedule.
The developed machine is equipped with a laser profilometry and a touch sense for on-line measurement of the shapes of sheet metal products. The proposed algorithm can deduce an tool-path schedule from the measured shapes of sheet metal products, by applying the techniques of neural networks. Experimental results show that the proposed algorithm is capable of deducing automatically an adequate tool-path schedule by which unfavorable deformation modes, such as wrinkles, can be avoided. Furthermore, this approach is applicable to on-line adjustments of the shapes of sheet metal products during the finishing process.
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Report
(3 results)
Research Products
(10 results)
