Volume 14 Issue 4 May - July 2019
Research Paper
Vikas Kumar Sukhdeve*, S. K.
Ganguly**
* Bhilai Institute of Technology,
Durg, Chhattisgarh, India.
** Mechanical Engineering, Bhilai
Institute of Technology, Durg, Chhattisgarh, India.
Sukhdeve, V. M., and Ganguly, S. K.
(2019). Comparison of Process Parameter Optimization of a Jig Boring Process
Using Taguchi Based Grey Analysis and Genetic Algorithm. i-manager’s
Journal on Future Engineering and Technology, 14(4), 58-66.https://doi.org/10.26634/jfet.14.4.14803
Abstract
In the present work
few process parameters of a Jig Boring machine like 'Feed Rate', 'Depth of Cut'
and 'Cutting Speed' have been optimized for best possible values of few
performance parameters or target parameters like 'Vertical Reaction Force',
'Surface Roughness' and 'Material Removal Rate' for a Mild Steel work specimen.
The grade of the steel used in the specimen is AISI 1040. Though optimization
of process parameters of a Jig Boring machine has been done by many researchers
or engineers previously, in the present work a mathematical model has been
formulated by regression analysis from the experimental data created as per
Taguchi method. Next, from the experimental data, Grey Relational Analysis has
been done to predict the optimum combination of process parameters for the best
result of performance parameters. Lastly, to validate the mathematical model
which has been derived by regression analysis, optimization of the process
parameters have been done using Genetic Algorithm optimization tool of MATLAB
Program and the optimum result of the process parameters have been verified
with the optimum result determined by Grey Relational Analysis.