Manufacturing Technology Today

K. Rama Kotaiah ¹, K. J. Babu ¹, J. Srinivas ², Kolla Srinivas ³

Affiliations
1 Dept. of Industrial and Production Engg., K. L. College of Engg., Vaddeswaram, Guntur (Dist), Andhra Pradesh, IN
2 Dept. of Mechanical Engg., NUY University, KR
3 Dept. of Mechanical Engg., R V R & J C College of Engg., Chowdavaram, Guntur (Dist), Andhra Pradesh, IN

Abstract

This paper presents an experimental investigation aimed at identifying and isolating effects of cutting conditions and over hanging length of work piece and over hanging length of tool on cutting forces and vibrations from those arising as a result of cutting tool wear. Machining test cuts were conducted using sharp tool and the effects of cutting conditions (depth of cut, cutting speed and feed rate), tool overhanging length and work piece over hanging length studied. Here experiments were conducted on EN8 steel, EN24 Steel, Mild steel and Aluminium at different cutting parameters and different overhanging lengths. Here chatter starting point length is measured from the free edge of the work piece and graphs were plotted between over hanging length verses cutting forces and chatter starting point length.

Full Text

     

K. Rama Kotaiah ¹, J. Srinivas ², K. J. Babu ³, Srinivas Kolla ⁴

Affiliations
1 K. L. Coilege of Engg., Vaddeswaram, Guntur (Dist), Andhra Pradesh, IN
2 Dept, of Mechanical Engg., NUY University, South Korea, US
3 Dept. of Indl. and Production Engg., K. L. College of Engg., Vaddeswaram, Guntur (Dist), Andhra Pradesh, IN
4 Dept. of Mechanical Engg., RVR & JC College of Engg., Chodawaram, Guntur (Dist), Andhra Pradesh, IN

Abstract

This paper presents effects of various cutting conditions (such as Velocity, Feed, Depth of cut), and tool geometry (such as Side Cutting Edge angle. Inclination angle. Rake angle), overhanging distance of work piece and over hanging distance of tool on regenerative chatter (Self excited vibrations) in turning process. A low mass accelerometer is placed at the tool-tip of the assembly and the system is excited at the same point by using an impulse hammer to obtain the tool-point frequency response function through spectrum analyzer or modal testing software. New test is performed when tool-overhang length changes or for different combination of system components. Regarding the analytical aspects, have to obtain any model of cutting process.This paper also presents mathematical modelling for better understanding the relationship between various cutting conditions, cutting forces and vibrations in turning machines.

Full Text

     

K. Rama Kotaiah ¹, J. Srinivas ², K. Jayanendra Babu ¹

Affiliations
1 Department of Industrial and Production Engg., K.L. College of Engineering, Vaddeswaram, Guntur (Dist.), IN
2 Department of the Mechanical Engineering, Chaitanya Engineering College, Visakhapatnam, IN

Abstract

This paper presents, a control methodology based on experimental data of the tool wear as a function of cutting variables. In automatic machine tools, there is strong need to control the tool wear by adjustment of the cutting parameters. In this connection, a control system, which can adjust the cutting parameters for a desired wear rate, is necessary. A regression relation is also established between the flank-wear, and the cutting parameters. An inversely trained neural network model, which supplies the modified values of the cutting parameters, is used as a controller. The results are shown in the form of tables and graphs.

Full Text

     

J. Srinivas ¹, K. Rama Kotaiah ²

Affiliations
1 Department of Mechanical Engineering, SCSVMV (Deemed University), Enathur, Kanchipuram, Tamilnadu, IN
2 Department of Industrial and Production Engineering, KL College of Engineering, Vaddeswaram-522502, Guntur (Dist)., Andhra Pradesh, IN

Abstract

The tool wear is significantly influenced by the cutting parameters like velocity, feed and depth of cut. Direct method of detecting the tool wear using tool makers microscope is not recommended in many situations. It has been observed that as tool wear begins for the same cutting parameters, the parameters like spindle power, cutting forces, surface roughness change abruptly. Hence the variations in these parameters indicate wear states qualitatively. In this paper some indirect methods of detecting tool wear status are proposed. A neural network model is developed to predict the spindle current and cutting forces for a given cutting parameters, so as to indicate levels of the tool wear. Also the tool wear can be indirectly estimated through finite element analysis, since the tool wear is influenced by stresses on the tool faces. Two-dimensional orthogonal cutting model is chosen with appropriate tool and work piece boundary conditions and material combinations. The deformations at the flank face are recorded for various values of tool chip contact lengths. The results are reported in the form of graphs and tables.

Full Text