Kamal Mahal

In present scenario CNC turning operation plays a vital role in metal based manufacturing industries. Therefore selection of optimum machining parameters, Tool geometry and cutting condition etc. for the variety of materials is an important and complicated task for the manufacturing industries in providing best quality at less cost to the customers. In this research work CNC turning operation is carried out using L9 Taguchi orthogonal arrays on Naval brass C360 coated carbide insert and influence of CNC turning process parameters like Cutting Speed, Feed and Depth of Cut are analysed for two output objectives like material removal rate and surface roughness. The optimum sets of turning process parameter as well as combined effect of considered response are estimated using Taguchi technique application. In this analysis it is found that depth of cut has the largest effect on metal removal rate and feed rate has the largest effect on the surface roughness.It can be observed that depth of cut has the largest effect on metal removal rate and feed rate has the largest effect on the surface roughness of C360 brass by turning on CNC. The optimum turning condition for material removal rate isspindle speed (1600 rpm), feed rate (0.20 mm/rev.) and depth of cut (0.8 mm). The optimum condition for surface roughness is spindle speed (1400 rpm), feed rate (0.20 mm/rev.) and depth of cut (0.2mm).

Aluminum alloys are broadly used in aerospace industry, automotive industry, railways and in marine industry due  to  its  resistance  to  corrosion,  light  weight  and  high strength to weight ratio. The aim of the present research is to optimize  the  process  parameters  for  higher  tensile  strength and to analyze the effect of process parameters such as tool rotational  speed,  welding  speed  and  tool  tilt  angle on  the tensile  strength  of  friction  stir  weldments. Taguchi  L9 orthogonal array was used to conduct the experiments. The optimum  process  parameters for  the  maximum  tensile strength  of  the  joints  were  predicted,  and  the  individual significance of each process parameter on the tensile strength of the friction stir weldment was evaluated by using the signal-to-noise ratio and analysis of variance (ANOVA) results

The experimental investigation of material removal rate, and micro hardness during machining of OHNS steel using
EDM machine was study in this paper. The input parameters include peak current, pulse on time; voltage gap and
flushing pressure were used for experimental work. Mean effect plot and S/N ratio graphs have been used to
optimize the machining parameters of EDM on OHNS steel using the Taguchi method and ANOVA methods. It can
be observed that Current has the largest effect on the material removal rate of OHNS steel by machining. It can be
observed that flushing pressure has the largest effect on the hardness of OHNS steel by machining. The optimum
machining condition for material removal rate (MRR) with positive polarity are Current (30 A), Pulse-on (100 µs)
Voltage Gap (10 v) and flushing pressure (20 lb/in2). The optimum machining condition for with positive polarity
for hardness are, Current (10 amp.), Pulse-on (100 µs), voltage gap (20 volt) and flushing pressure (10 lb/in2).

Aim of the experimental investigation was to determine the
effect of electric discharge machining parameters on surface
roughness of oil hardened non shrinkable (O6) steel. Though
vast research has been done to improve the surface finish of hard
metal machined by EDM, optimal choice of parameters for best
performance measures is still challenge. The experiments were
carried out on adequate range of machining parameters. Selected
input parameters for this study were peak current, pulse-on-time,
and pulse-off-time. Pure copper electrode with positive polarity
in dielectric medium was used to perform the investigation. The
optimal machining parameters peak current (8 Amp), pulse on (45
μs) and pulse off (9 μs) were originated by using Taguchi method
and ANOVA analysis. Design of experiment approach was used to
model the experimental data. It is found that interactions between
Peak current, pulse on, Voltage Gap and Flushing Pressure have
significant effect on the surface roughness.