NANO-ENHANCED COOLANT FOR ENVIRONMENTAL-FRIENDLY MACHINING

ABSTRACT
Application of cutting fluids as cooling and lubricating media is considered essential in manufacturing practices on
account of providing lubrication, heat transfer capabilities, corrosion minimization as well as flushing away of metal chips
and debris. Due to the sizable costs of these cutting fluids with respect to production costs, increasing eco-awareness,
implementation of sustainability indices in manufacturing units and strict regulations due to detrimental effects of cutting
fluids to the environment and the human exposure, the manufacturing units are in a continuous pursuit for finding out
economically viable substitute to cutting fluids. Minimum quantity lubrication (MQL) technique offers a near-term
solution to the problem. MQL is a sustainable manufacturing technique where miniscule quantity of fluid atomized in
compressed air flow is supplied to the cutting zone resulting in a meagre amount of airborne mist on shop floor. This
product presents nanofluid-MQL machining performance to that of the conventional flooded machining conditions in end
milling machining process of aluminum alloy 6061 T6.

METHODOLOGY
Uncoated WC-Co 6.0% tool and PVD coated carbide cutting tools are tested using 23.4-54.0 ml/hr flow rate of
commercial vegetable oil and nanofluid (TiO2 based) for MQL machining using uncoated tool, with different combinations
of input cutting parameters. PVD coatings are of two types; single layer TiAlN coating and dual layered TiAlN+TiN coating
on cemented carbide substrate. Metal cutting performance and tool damage of the uncoated and coated carbide inserts
are compares in MQL machining. PVD coated tools outperform the uncoated tool in terms of tool damage and surface
quality. Response surface methodology with central composite design approach is used for the design of experiments.
Random variable models are used to correlate the flank wear and surface roughness of the machined work piece. Multicriteria
decision making approach is used to select single best compromised solution among the solutions located on the
Pareto frontiers.

FINDINGS
As a result of the experiments, regression models for the prediction of machining responses i.e. surface roughness,
material removal rate and flank wear, are developed in terms of cutting speed, feed rate, depth of cut, MQL flow rate for
different cooling conditions. The developed second order prediction models show a good agreement with the
experimental results and are validated statistically and experimentally.
Comprehensive multi-objective optimization technique using genetic algorithm is performed to optimize machining
performance measures under different MQL conditions, based on Pareto optimal design approach, integrating the effects
of all machining parameters.
As a result of optimization,
(1) Surface roughness obtained in nanofluid MQL is 24.67 % and 1.5 % lower than flooded conditions at minimum
and maximum depth of cut respectively.
(2) Maximum surface roughness obtained with nanofluid MQL is 22.51 % lower than conventional MQL.
(3) With uncoated tungsten carbide insert in conventional MQL at 0.83 ml/min, the reduction in surface roughness
at minimum feed rate is 26.3 % while surface roughness at maximum feed rate is 14 % higher in conventional
MQL as compared to flooded conditions.
(4) Maximum surface roughness produced by nanofluid machining at maximum feed rate is 27.9 % lower than
conventional MQL machining with 0.65 ml/min. Maximum surface roughness produced by nanofluid MQL
conditions is 18 % lower than maximum in flooded conditions.
(5) At maximum speed, an improvement of 19.6 % is noted in surface roughness with nanofluid MQL machining
compared to conventional MQL. The performance of uncoated tungsten carbide insert in nanofluid MQL
machining is comparable to coated inserts in conventional MQL machining. Maximum surface roughness in
nanofluid MQL machining is 43.37 % reduced as compared to conventional MQL.