B SATHEESH KUMAR
@nbkrist.co.in
Associate Professor in Mechanical Engineering
NBKRIST
RESEARCH, TEACHING, or OTHER INTERESTS
Mechanical Engineering, Mechanical Engineering, Mechanical Engineering, Mechanical Engineering
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
B. Satheesh Kumar, Neelam Parimala, and P. Vamsi Krishna
Springer Singapore
G. Reddy, V. D. Reddy, B. S. Kumar and J. Shyamsunder
In this work, characteristics of various ball bearing parameters are studied under different loads and rotational speeds. By using Dimensional Analysis (DA), dimensionless parameters are computed which provides solution for a group of parameters. This analysis can be accomplished by using the Buckingham π-theorem. DA leads to reduction of the number of independent parameters involved in a problem. These independent parameters get expressed as dimensionless groups. These dimensionless groups are always ratios of important physical quantities involved in the problem of interest. In modeling and experimentation, its main function is to reduce the amount of independent variables, simplify the solution, and generalize the results. It becomes an effective method, especially if a complete mathematical model of the investigated process is not known. Moreover, in the present work the Buckingham π-theorem is applied to find the influencing parameter π5 by using the Taguchi method.
B. Satheesh Kumar, , G. Padmanabhan, P. Vamsi Krishna, , and
Universiti Malaysia Pahang Publishing
This paper aims to obtain the optimal combination of machining parameters for multiple performance characteristics in the turning operation by implementing desirability function analysis. Experiments were conducted using machining parameters like different proportions (5%, 10%, and 15%) of extreme pressure additive in three different vegetable oil based cutting fluids (sesame, canola, and coconut oils), cutting speed and feed rate for evaluating the cutting force, cutting tool temperature, tool flank wear, and surface roughness. An orthogonal array (L27) was generated using the Taguchi design to carry out the experiments on AISI 1040 steel. Composite desirability was analysed for identifying the optimal levels of machining parameters. Experimental results revealed that cutting fluid had the most significant effect on cutting force, cutting tool temperature, tool flank wear, and surface roughness. Confirmation test was carried out to validate the results. Experimental results have shown that machining performance can be improved through desirability function analysis.