๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Analysis of forces in ultrasonically assisted turning

โœ Scribed by N. Ahmed; A.V. Mitrofanov; V.I. Babitsky; V.V. Silberschmidt


Publisher
Elsevier Science
Year
2007
Tongue
English
Weight
290 KB
Volume
308
Category
Article
ISSN
0022-460X

No coin nor oath required. For personal study only.

โœฆ Synopsis


Many modern engineering materials are very difficult to process with conventional machining methods. Ultrasonically assisted turning (UAT) is a new technology, where high frequency vibration (frequency fE20 kHz, amplitude aE15 mm) is superimposed on the movement of the cutting tool. Compared to conventional turning (CT), UAT allows significant improvements in processing many intractable materials, such as high-strength aerospace alloys and composites, by producing a noticeable decrease in cutting forces and a superior surface finish. Vibro-impact interaction between the tool and workpiece in UAT during the chip formation leads to a dynamically changing cutting force in the process zone as compared to the quasistatic one in CT. The paper presents an experimental study and computational (finite-element) model of both CT and UAT. Forces acting on the cutting tool in UAT are studied, and their dependence on vibration amplitude, frequency and vibration direction as well as on cutting parameters, such as feed rate and cutting speed, are investigated.


๐Ÿ“œ SIMILAR VOLUMES


FEM analysis of ultrasonic-vibration-ass
โœ S. Amini; H. Soleimanimehr; M.J. Nategh; A. Abudollah; M.H. Sadeghi ๐Ÿ“‚ Article ๐Ÿ“… 2008 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 624 KB

Ultrasonic assisted turning (UAT) is an advanced method developed for machining tough and brittle materials such as supper-alloys, ceramics and glass. Using MSC-Marc and Ansys, the authors studied machining of IN738 with a tool vibrating at ultrasonic frequency. The machining forces and stresses act

The use of neural networks in predicting
โœ Y.S. Tarng; T.C. Wang; W.N. Chen; B.Y. Lee ๐Ÿ“‚ Article ๐Ÿ“… 1995 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 560 KB

The purpose of this research is to develop a predictive turning-force model based on neural networks. In the first stage of the research, a cutting-force model based on orthogonal machining theory is studied. Turning forces can be estimated from this model using complex computational procedures when