Abstract:
Grinding is one of the most rigorous machining processes where material is
removed from a surface with constant friction and rubbing of abrasive grits attached to a
cylindrical grinding wheel. High temperature is generated at the workpiece-wheel interface
due to this rubbing and friction. This high temperature generated in the grinding zone
adversely affects the physical properties of the ground surface in terms of induced surface
and sub surface residual stress, surface roughness, micro cracks and dimensional deviation.
So the control over this temperature is a matter of great interest of researchers in the recent
years. Conventional sulfur based cutting fluid has several detrimental effect on
environment like soil contamination and disposal of toxic gases in the atmosphere. They
also have severe impact on the human health of who perform machining in the wet
condition. So the application of alternate cooling environment like Cryogenic cooling
(Liquid N2), High pressure coolant (HPC), Minimum Quantity Lubrication (MQL),
Compressed Cold Air are studied by many researcher and their performance is evaluated
with process parameters like Tangential and normal grinding forces, residual stress,
surface roughness, surface bum and wheel loading. The application of MQL in grinding
operation has both economical and environmental advantages over the. other cooling
techniques. The performance of MQL in respect of grinding temperature, surface
roughness, residual stress and other performance parameters are studied by researchers for
different wheel-work combinations but not in extensive way. Still there are scopes to
investigate new combinations to assess the performance of MQL cooling environment in
plane surface grinding. Numerical modeling of cutting temperature under MQL condition
is still in developing stage. This research mainly focuses on the numerical and predictive
modeling of grinding zone temperature and surface roughness for grinding medium carbon
XVI
steel at industrial speed and feed under MQL cooling condition with two different type of
wheel. The experimental result indicates that grinding AISI 1045 steel under MQL
condition is more effective and generates much lower grinding zone temperature compared
to grinding under dry condition. Again for both dry and MQL environment CBN wheel
results lower grinding zone temperature than Alumina wheel. A finite element model is
developed by ABACUS/CAE to numerically predict the temperature distribution of the
grinding zone along the contact length In MQL environment. The model is validated by
comparing with the result obtained from traditional heat transfer model and found to be
satisfactory. Based on the experimental result of Surface roughness for grinding AISI 1045
steel under MQL condition a predictive Response Surface model is developed. Three
process parameters are considered for surface roughness prediction such as, Wheel speed,
work speed and infeed. Strong interaction is found between the listed parameters and their
main effect is also found prominent to predict desired surface roughness value. The model
is then checked and validated by comparing with experimental data and found reasonably
accurate with slight variation which is the general consequence of any natural process.
