Parametric study of surface roughness in turning of az31 b mg alloy under different cooling conditions

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Parametric study of surface roughness in turning of
AZ31B Mg alloy under different cooling conditions
by
Imran Sarker 14.01.07.065
M.A. Nasher Khan Pathan 14.01.07.094
MoinAkter 11.02.07.069
A Thesis
Submitted to the
Department of Mechanical & Production Engineering
In Partial Fulfillment of the
Requirements for the Degree
of
BACHELOR OF SCIENCE IN INDUSTRIAL & PRODUCTION ENGINEERING
DEPARTMENT OF MECHANICAL & PRODUCTION ENGINEERING
AHSANULLAH UNIVERSITY OF SCIENCE & TECHNOLOGY
DHAKA 1208, BANGLADESH

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This thesis work entitled Parametric study of surface roughness in turning of AZ31B Mg
alloy under different cooling conditions submitted by the following student has been accepted
as satisfactory in partial fulfillment of the requirement for the degree of B. Sc. in Industrial &
Production Engineering on May 03, 2018.
Imran Sarker
14.01.07.065
M.A. Nasher Khan Pathan
14.01.07.094
MoinAkter
11.02.07.069
Mozammel Mia
Assistant Professor
Ahsanullah University of Science & Technology
Dhaka, Bangladesh.

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Declaration
We do hereby declare that this thesis work has been done by us and neither this thesis nor any
part of it has been submitted elsewhere for the award of any degree or diploma.
Imran Sarker
14.01.07.065
M.A. Nasher Khan Pathan
14.01.07.094
MoinAkter
11.02.07.069
Mozammel Mia
Assistant Professor
Ahsanullah University of Science & Technology
Dhaka, Bangladesh.

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Contents
List of Tables ……………………………………………………………… I
List of Figure ……………………………………………………………… II
Acknowledgement ……………………………………………………………… III
Abstract ……………………………………………………………… IV
Chapter 1 Introduction 11-13
Chapter 2 Literature Review 14-23
Chapter 3 Methodology 24-29
3.1 Material 24-26
3.2 Machine 26-27
3.3
3.4
3.5
Tool holder
Insert
Workpiece
27-28
28
29
3.6 Experimental Setup 29
3.7 Surface roughness measurement machine 30
Chapter 4 Result and Discussion 31-58
4.1 Average surface roughness parameter, Ra 31-35
4.2
Root mean square roughness parameter, Rq
35-40

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4.3 Average maximum height surface roughness, Rz 40-44
4.4 Maximum height of the surface parameter, Rt 45-49
4.5 Maximum profile peak height, Rp 49-53
4.6 Maximum profile valley depth, Rv 53-58
Chapter 5 Conclusion 59
Reference 60-64

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List of Tables
Table 3.1.1 : Physical properties of Magnesium alloy AZ31B
Table 3.1.2 : Chemical composition of Magnesium alloy AZ31B
Table 3.1.3 : Thermal properties of Magnesium alloy AZ31B
Table 3.1.4 : Mechanical properties of Magnesium alloy AZ31B
Table 3.2.1
Table 3.7.1
:
:
Specification of Lathe machine
Specification of Surface roughness measurement machine
Table 4.1.1 : Response Table for mean of means of average surface roughness (Ra)
Table 4.2.1 : Response Table for mean of means of root mean square roughness (Rq)
Table 4.3.1 : Response Table for mean of means of average maximum height (Rz)
Table 4.4.1 : Response Table for mean of means of the maximum height of the
surface (Rt)
Table 4.5.1 : Response Table for mean of means of the maximum profile peak height
(Rp).
Table 4.6.1 : Response Table for mean of means the maximum profile valley depth
(Rv)

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List of Figures
Fig.1.1 : Turning operation
Fig. 3.2 : Lathe machine
Fig.3.3 : Tool holder
Fig. 3.4 : Coated carbide insert
Fig. 3.5 : Magnesium alloy AZ31B workpiece
Fig. 3.6 : Machie Tool setup
Fig. 3.7 : Surface roughness measurement machine
Fig. 4.1.1 : Main effects plot for the arithmetic mean of roughness parameter (Ra)
Fig. 4.1.2 : Contour plot of Ra vs feed and depth of cut
Fig. 4.1.3 : Surface Plot of Ra vs Feed, Depth of Cut
Fig. 4.2.1 : Main effects plot for the root mean square roughness (Rq)
Fig. 4.2.2 : Contour Plot of Rq vs Feed, Cutting Speed
Fig. 4.2.3 : Surface Plot of Rq vs Feed, Depth of Cut
Fig. 4.3.1 : Main effects plot for the ten-point mean roughness (Rz)
Fig. 4.3.2 : Contour Plot of Rz vs Feed, Depth of Cut
Fig. 4.3.3 : Surface Plot of Rz vs Feed, Depth of Cut
Fig. 4.4.1 : Main effects plot for the maximum height of the profile (Rt)
Fig. 4.4.2 : Contour Plot of Rt vs Feed, Depth of Cut
Fig. 4.4.3 : Surface Plot of Rt vs Feed, Depth of Cut
Fig. 4.5.1 : Main effects plot for the maximum profile peak height (Rp)
Fig. 4.5.2 : Contour Plot of Rp vs Feed, Depth of Cut

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Fig. 4.5.3 : Surface Plot of Rp vs Feed, Depth of Cut
Fig. 4.6.1 : Main effects plot for the maximum profile valley depth (Rv)
Fig. 4.6.2 : Contour Plot of Rv vs Feed, Depth of Cut
Fig. 4.6.3 : Surface Plot of Rv vs Feed, Depth of Cut

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Acknowledgement
We would like to thank our thesis supervisor Mr. Mozammel Mia, Assistant Professor, MPE,
AUST for his contribution in the idea generation of the current research work and making this
work successful. We also express sincere thanks to Mr. Md. Abul Kalam, Assistant Foreman
Instructor, Machine Tools Lab, MPE, AUST for his direct help in conducting the experiment.
Finally, the heart-felt gratitude to department of MPE, AUST for providing us such experimental
facilities.
Authors

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Abstract
The Mg alloys have intensive application in industrial sectors especially where the weight of the
parts count. Therefore, globally, significant amount of Mg alloy is processed to impart required
shape via machining. In that respect, in the current study, the turning of Mg alloy AZ31B is
performed and different parameters of surface roughness are studied. Here, the cooling-
lubrication conditions are varied as dry, wet, minimum quantity lubrication (MQL). The MQL is
studied due to its capability of improving the machining performance in sustainable manner.
Though MQL is reported in many studies, it was hardly employed in machining of Mg AZ31B
alloy. To fill this gap, this study is conducted. The straight turning of cylindrical work material
was conducted by using coated carbide insert, and the design of experiment was full factorial
method. The controllable variables were cutting speed, feed rate, depth of cut and cooling
conditions, each with three levels. The studied responses were arithmetic mean of roughness
parameter(Ra), root mean square surface roughness parameter(Rq), ten-point mean roughness
parameter (Rz), maximum height of the profile parameter (Rt), maximum profile peak height
parameter (Rp), and lastly the maximum profile valley depth parameter (Rv).In this study, the
effects of each factor on the responses are analyzed using main effect plot, contour plot, 3D
surface plot and by using Taguchi signal/noise assisted response table. Based on these analysis, it
was found that the feed rate exerted the highest influence on the roughness parameters, and the
MQL showed improved performance in producing better quality surface compared to dry and
conventional flood cooling. Hence, it is recommended to employ MQL in turning of AZ31B Mg
alloy with lower feed rate.

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Chapter 1
Introduction
Magnesium AZ31B alloy is mainly used in aerospace applications and general commercial
applications. As can be seen the use of magnesium is predicted to rise at a similar rate to that of
other metals well into the new century. This presumes continued investment in research and
development. So this report aims to experiment different operation on AZ31B magnesium alloy
in different conditions to help the much needed investigation for further development.
Magnesium is the lightest of all metals used as the basis for constructional alloys. Magnesium
alloys are mixtures of magnesium with other metals (called an alloy), often aluminum, zinc,
manganese, silicon, copper, rare earths and zirconium. Magnesium alloys have a hexagonal
lattice structure, which affects the fundamental properties of these alloys. Plastic deformation of
the hexagonal lattice is more complicated than in cubic latticed metals like aluminum, copper
and steel; therefore, magnesium alloys are typically used as cast alloys, but research of wrought
alloys has been more extensive since 2003. It is this property of constructing numerous alloys
which entices automobile manufacturers to replace denser materials, not only steels, cast irons
and copper base alloys but even aluminum alloys by magnesium based alloys. The requirement
to reduce the weight of car components as a result in part of the introduction of legislation
limiting emission has triggered renewed interest in magnesium. The fact that the magnesium has
good electromagnetic interference makes it also very attractive to the audio and electronic
industries.

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Magnesium alloy components are usually produced by various casting processes. International
Magnesium Association (IMA) analysis of magnesium consumption indicates that the use of die
casting magnesium alloys in automotive components continues to grow at an unprecedented
annual rate. It means that high-pressure die casting continues to remain the brightest star for
magnesium alloys in terms of long-term potential growth.
The advantages of magnesium and magnesium alloys are listed as follows, lowest density of all
metallic constructional materials; high specific strength; good cast ability, suitable for high
pressure die-casting; can be turned: milled at high speed; good weld ability under controlled
atmosphere; much improved corrosion resistance using high purity magnesium; readily
available; compared with polymeric materials: better mechanical properties; resistant to ageing;
better electrical and thermal conductivity; recyclable.
One of the reasons for the limited use of magnesium has been some poor properties exacerbated
by a lack of development work. The disadvantages of magnesium are presented based on the
following: low elastic modulus; limited cold workability and toughness; limited high strength
and creep resistance at elevated temperatures; high degree of shrinkage on solidification; high
chemical reactivity; in some applications limited corrosion resistance.
This report contains specifically about the study of magnesium alloy AZ31B.Magnesium AZ31B
alloy is available in different forms such as plate, sheet, and bar. It is an alternative to aluminum
alloys as it has high strength to weight ratio. It is widely available when compared to other
magnesium grades. Magnesium AZ31B alloy has good machinability. It is flammable, so
extreme care should be taken while performing this process. A lubricant is used to perform
machining process. The machinist is required to constantly monitor the operation with a
magnesium fire arresting kit. Magnesium AZ31B alloy can be formed by preheating at 260°C

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(500°F).Magnesium AZ31B alloy can be welded using metal arc and gas tungsten arc welding
techniques. This alloy is stress relieved at 149°C (300°F) for 30 to 60 minutes followed by
cooling in air. Full annealing can be done at 344°C (650°F) followed by slowly cooling in the
furnace.
Turning is a machining process used to make cylindrical parts, where the cutting tool moves in a
linear fashion while the workpiece rotates. Commonly performed with a lathe, turning reduces
the diameter of a workpiece, typically to a specified dimension, and produces a smooth part
finish. A turning center is a lathe with a computer numerical control. Sophisticated turning
centers can also perform a variety of milling and drilling operations. Here, turning of magnesium
alloy AZ31B is expected to be performed under appropriate experimental conditions.
Fig. 1.1: Turning operation.

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Chapter 2
Literature review
A number of studies have been performed regarding machining of Mg alloys. Some of those
studies are for conventional machining such as turning, milling, drilling and grinding. On the
other side, some studies were focused on the modern machining processes namely the electrical
discharge machining, electro-chemical machining. Then, other researchers have concentrated on
the studies of mechanical behaviors, whereas other groups have investigated the material
composition and their effects on final machinability.
Pu et al. (Pu et al., 2012)have worked to carry out experimental investigations for the enhanced
surface integrity of AZ31B Mg alloy while machining. Spraying liquid nitrogen onto the
machined surface from the clearance side of the tool significantly reduced the maximum surface
temperature on AZ31B Mg alloy from 125 °C to 52 °C during machining .Application of liquid
nitrogen reduced the surface roughness by about 20% compared to dry machining using both 30
mm and 70 mm edge radius tools. By this process a nameless layer which is similar to the ‘white
layer’ of machined steel, formed on the surface of the AZ31B Mg alloy under cryogenic
condition. Cryogenic machining with large edge radius tools led to the most desirable surface
integrity on AZ31B Mg alloy including improved surface finish, nanocrystalline grain structures,
strong basal texture and compressive residual stresses. The study suggests that cryogenic
machining promotes tool life and by cryogenic cooling may also boost the surface integrity of
machined products. However, by signal to nose ratio(S/N) and ANOVA analysis it’s been seen

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that tool rotational speed has the most significant influence on the surface integrity. So, if we can
optimize these parameters, the surface integrity of Mg alloy can be increased.
Kheireddine et al. (Kheireddine, Ammouri, Lu, Jawahir, & Hamade, 2013)performed a
combined experimental and numerical study on the surface hardness of in process cryogenic
cooling while drilling in Mg AZ31B alloy. At the surface of the drilled holes, micro- hardness
measurements were experimentally done for different feed values. In comparison of the
experimentally measured hardness values with the results from a FEM (Finite element method)
model, the FEM model does well. Such values showed significant increase in surface hardness
for cryogenically cooled holes compared with those drilled in the dry condition (with both dry
and cryogenically cooled hole surfaces being noticeably harder than that of bulk Mg). However,
this method works well on experimenting the surface hardness in cryogenic cooling. But instead
if we use MQL method it would be greater. Because MQL is the process of applying minute
amounts of high-quality lubricant directly to the cutting tool/work piece interfaces. So, MQL
method the costing of machining in cryogenic condition will be reduced. Also, the machining
environment/surroundings will be clear and eco-friendly.
To observe the interactions between workpiece material and tool material and coating,
respectively, Tönshoff et al. (Tönshoff & Winkler, 1997) carried out turning operations for
machining the alloy AZ91 HP. Here the turning experiments were done in a CNC inclined-bed
lathe machine. Main power was, P=5o kW and max no of revolutions, n= 10000/min. In this
process the influence of the cutting tool and material and coating gives different results. If
uncoated and TiN-coated carbides are used flank build-up can be observed. If PCD
(Polycrystalline Diamond)-tipped tools are used, adhesive effects can’t generally be avoided if
workpiece material gets into contact with the carbide body. PCD-coated tools show a superior

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behaviour. No adhesion of magnesium on the flank occurs. When turning AZ91 HP, tool wear
cannot be observed due to low machining forces. From this investigation it’s certain that PCD
coated cutting tools show a premium behaviour while machining at dry conditions even at higher
speeds of, Vc> 900 m/min. Also, if PCD coated tools are used, adhesion between tool and work
piece can be avoided. When machining magnesium alloys, PCD tools should be preferred due to
best resistance against abrasion, good surface roughness, good thermal conductivity and low co-
efficient of friction. Tools with PCD inserts give best tool life travels too. Yet, for complex tool
geometry PCD coatings have some limitations (e.g. for drilling). Then the PCD coatings should
be at least 20 micro meters thick.
Dinesh et al. (Dinesh, Senthilkumar, Asokan, & Arulkirubakaran, 2015)used cryogenic liquid
while turning ZK60 Mg alloy in this paper. Use of this cryogenic liquid during machining
improves the surface characteristics of newly formed machined surface. In addition to the
cooling of workpiece and tool surfaces, they act as effective lubricant between contact surfaces.
By this turning operation of ZK60 Mg alloy under various cutting speed and feed; cutting force,
cutting temperature, surface roughness, effect of cryogenic liquid on heat affected zone, grain
size of the machined surface was investigated. ZK60 Mg alloy rod of 20 mm diameter, 120 mm
of length was the work piece here. Turning experiments were conducted in LEADWELL CNC
turning centre with ISO K20 CNMA 120408 uncoated tungsten carbide inserts under various
machining conditions. Each machining experiment was conducted three times and the average
response value was noted. In comparison with the dry condition, in cryogenic condition the
cutting temperature rise was less. Thrust force and main cutting force are found to be increasing
when the feed rate increases due to strain hardening effect in both dry and cryogenic machining
conditions. During machining when cutting speed increases from 60 m/min to120 m/min both

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the cutting forces (Thrust force, Ft and the main force, Fc) are reduced due to thermal softening
effect of work piece material. When the speed increases, temperature at tool-work piece interface
also increases which causes material softening and reduces the force required to remove the
material. Also, 20-40% reduction of surface roughness was achieved during cryogenic lubricant
(Liquid N2) machining in comparison with dry condition machining. In cryogenic condition a
featureless layer with the grain size in sub-micron/Nano range can be produced. However, this
process can also be run by MQL method for cleaner machine environment and for less costly
machining operation.
Villeta et al. (Villeta, De Agustina, De Pipaón, & Rubio, 2011)investigated efficient optimisation
the dry turning of Mg pieces to acquire a surface roughness within technical requirements. The
experimental turning processes in this study were applied to cylindrical bars with a diameter of
40 mm and a length of125 mm (useful length of 100 mm) made from UNSM11311 Mg alloy.
For safety, economic and environmental reasons, machining of magnesium should be under dry
conditions. Because while machining, due to their flammability at high temperatures and the
great ease with which their chips and dust auto-ignite. In these case, the use of water or water
based coolants can cause risk problems as Mg decomposes water to form hydrogen gas, which is
highly explosive. The average roughness on this experiment was, Ra= 1.2 micro meter. If finer
surface finish is to be done, then the production cost of Mg alloy materials rapidly rises. Here for
experiment the Taguchi design was selected. This type of design uses prior information from the
process to improve the design efficiency. Feed rate, cutting speed and tool coating were included
in the experimental design because they were the most important machining parameters. Low
feed rates, cutting speeds and cut depth were applied in this study while keeping the depth of cut
fixed at 0.25 mm; similar conditions are used by aerospace companies to carry out repair and

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maintenance operations on magnesium alloy pieces due to its high manufacturing costs. An
EMCO Turn 120 CNC lathe, equipped with an EMCO Tronic T1 numerical control module,
machined the Mg bars, and a MitutoyoSurftest SJ-401 surface roughness tester measured the
roughness. The feed rate was the process parameter with the greatest influence on the surface
roughness: as the feed rate increased,the target roughness value (Ra=1.2 micro meter) was more
closely met with minimum variability in the experimental range. As for tool selection, tools for
steels(TP200 and TK2000) were better than tools for non-ferrous alloys (HX), which is useful
when considering inserts. The combinations of cutting conditions that achieved the optimal
surface roughness was as follows: 0.15 mm/rev—TP200 and0.15 mm/rev—TK2000
(independent of the cutting speed).Such combinations led to an expected value for the roughness
Ra between 0.975 and 1.425 micro meter, with a probability of at least95%; therefore, surface
roughness will be within 0.8 μm<Ra<1.6 μm at a very high percentage. However, this
investigation led to many chances of improving the machinability of Mg alloy for important
applications. But there was some lack of interaction between the tool coating and feed rate, lack
of interaction between cutting speed and feed rate. These lacking can be diminished with more
informative machining process.
In this paper, by Akyuz et al. (Akyuz, 2013)influence of Al content on the machinability of AZ
series cast Mg alloys was investigated. Cutting forces during turning operation and surface
roughness measurements carried out to evaluate the machinability of Mg alloys. Micro-structural
surveys on the Mg alloy were conducted on the metallographic samples by a Nikon Eclipse
LV150 type optical microscope after etching with 1 mL HNO3, 24mL and 75 mL ethylene
glycol solution. The tensile tests were performed at room temperature according to the ASTM E
8M-99 standard with a crosshead speed of 0.8mm/min (Shimadzu Autograph AGS-J 10

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kNUniversal Tester) on tensile test samples which have gage diameter and length of 8 mm and
40 mm, respectively. The averages of minimum three samples were taken in to account in the
determination of tensile values. Machining process was done by a 2.2 kW Boxford 250 CNC
lathe machine to determine the cutting forces under dry cutting conditions. Polycrystalline
diamonds (PCD) (Taegutec CCGT 120408 FL K10) were used as cutting tools in the turning
operations. Two types of experimental work have been carried out for evaluation of cutting
forces. One was that feed rate (f)and depth of cut (DoC) were kept constant to maintain cross-
sectional area of the chips in per revelation, while the other type was on the basis of constant f of
cutting tool at varied revelations and DoC’s. Mg alloys AZ21 & AZ91 was turned at 56 and 168
m/min. For AZ01 control sample, the cutting force was around 19.5 N (turned at 56 m/min)
which was the lowest cutting force among the alloys studied. Undoubtedly, FBU(Flank Build-
Up) was present in the surface of the cutting tools. FRIEMUTH and WINKLER reported that
FBU was a characteristic feature in machining Al-containing Mg alloys havingMg17Al12
eutectic phase at grain boundaries. TOMAC et al described that when certain Mg alloys were
cutting at high cutting speeds without the cutting fluid, FBU formed on the flank surfaces of the
tool. In conclusion, it was seen that the cutting forces increase as the cutting speed increases for
all the alloys studied which is applied to FBU at the tip of the cutting tool during machining. As
compared to Al-containing alloys, the cutting force was much lower for the AZ91 alloy than for
the AZ21 alloy. Also, roughness of the samples decreases with increasing cutting speed for all
the alloys studied. As Al content of the alloys increases, roughness value decreases considerably.
However, the turning operation of Mg alloy in this paper is pretty useful. But if this process is
carried out in Cryogenic or MQL condition the investigation would be more safe and precise.

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Pu et al. (Z. Pu et al., 2011) investigated the influence of cutting edge radius and cooling method
on surface integrity using AZ31B Mg alloy which were turned orthogonally by the help of two
edge radii cutting tools in both dry and cryogenic conditions. In cryogenic conditions using a
large edge radius tool led to a thicker grain refinement layer, larger compressive residual stresses
and stronger intensity of basal texture which may remarkably enhanced the corrosion
performance of magnesium alloys. In dry condition, large edge radius led to smaller compressive
residual stresses and a decrease in thickness of compressive layer, especially in the axial
direction. However, in this study, large radius tool in cryogenic conditions increases intensity of
the basal plane on the machined surface but not in dry conditions.
In this paper, Zhao et al. (Zhao, Hou, & Zhu, 2011) investigated the ignition conditions of
AM50A magnesium alloy at different cutting parameters. The relationship between ignition
conditions and chip morphologies was further explored. The macro morphologies of the chips
were observed by optical microscope and the micro structure were obtained by scanning electron
microscope (SEM). It is found that the macro morphologies of chips can be characterized into
powdered chip, tubular helical chip, acicular helical chip, and long belt chip, which correspond
to the different ignition conditions. The powdered chips and acicular spiral chips are easily
ignited. These results should be useful to avoid the chip ignition of Mg alloys during high speed
face milling. However it doesn’t mention chip ignition in any other form of milling which should
be investigated.
In this study, by Walter et al. (Walter & Kannan, 2011) the influence of surface roughness on the
passivation and pitting corrosion behavior of AZ91 magnesium alloy in chloride-containing
environment was experimented using electrochemical techniques. The study suggests that the
surface roughness plays a critical role in the passivation behavior of the alloy and hence the

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pitting tendency. An increase in the surface roughness of the AZ91 Mg alloy affects the
passivation tendency and consequently increases the pitting susceptibility of the alloy but when
the passivity of the alloy is disturbed then the influence of surface roughness on the pitting
corrosion susceptibly becomes less significant. However, this phenomena should be investigated
more to know about the influence of surface roughness on the pitting corrosion which
susceptibly becomes less significant when the passivity of the alloy is disturbed.
It has been reported by Pu et al. (Z. W. Pu et al., 2011) that reducing the grain size of AZ31B Mg
alloys could significantly enhance its corrosion resistance, which is often the limiting factor for
its wide application. In this study, the potential of cryogenic machining as a novel SPD (Severe
Plastic Deformation) method to induce grain refinement on the surface of AZ31B Mg alloys was
investigated. An FE model using the Johnson-Cook constitutive equation is developed to
simulate orthogonal turning of AZ31B Mg alloy under dry conditions which can successfully
predict the chip morphology and forces. However, the FE model should be further developed to
simulate the influence of liquid nitrogen cooling by adjusting the thermal boundary conditions
based on experimentally measured temperature data during cryogenic machining.
In this study, the influence of machining conditions in turning on surface integrity of a wrought
Mg-Zn-Zr-RE alloy was investigated by Wojtowicz et al. (Wojtowicz, Danis, Monies, Lamesle,
& Chieragati, 2013).This study suggests optimal cutting conditions to achieve a given surface
integrity and improve fatigue life through turned surfaces which were obtained through a design
of experiments, where input parameters are cutting speed, feed, depth of cut and nose radius.
After that modifications of surface integrity such as tensile/compressive residual stress, micro-
hardness, twinning and surface roughness were correlated with cutting parameters. However, the
selected cutting conditions should be reproduced on fatigue specimen, which should be tested in

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the future to confirm the expectation to improve fatigue strength, round edge radius with low or
medium cutting speed and low feed to limit surface defects.
In this paper, by Bhowmick et al. (Bhowmick, Lukitsch, & Alpas, 2010) the study of dry and
minimum quantity lubrication (MQL) drilling of cast magnesium alloy AM60 used in the
manufacturing of lightweight automotive components has been stated. Using distilled water
(H2O-MQL) and a fatty acid based MQL fluid (FA-MQL), both supplied at the rate of 10 ml/h,
the maximum and average torque and thrust forces were measured during drilling & compared
with those generated during flooded (mineral oil) drilling. So, the tool life during dry drilling
was inadequately short. The maximum temperature generated in the work piece during MQL
drilling was lower than that observed in dry drilling, and comparable to flooded condition. The
maximum temperature generated in the work piece during MQL drilling did not exceed that
produced during flooded drilling. Consequently, there was no softening of the material around
the holes during the course of drilling. The amount of magnesium transferred to the drill flutes
and BUE formation at the drill’s cutting edge were both significantly reduced, resulting in lower
torque and thrust force requirements for drilling. However, the suitable conditions should be
investigated for dry condition to prevent abrupt drill failure.
This study by Nasr et al. (Nasr & Outeiro, 2015) presents a sensitivity analysis of cryogenic
cooling effects on process mechanics, when cutting AZ31B-O magnesium alloy. Finite element
modeling was used to simulate orthogonal cutting of AZ31B-O under dry and cryogenic
conditions, where different parameters (cutting forces, temperatures, shear angle, chip
compression ratio and plastic deformation) were investigated. Cryogenic cooling results in lower
machined surface and tool rake temperatures, slightly shorter chip-tool contact length, tends to
induce higher tensile plastic strain in the machined surface.

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Based on the literature study, it is noticeable that several studies have concentrated on the
machining of Mg alloys, among which some have studied the AZ31B alloy. Their study was
mostly focused on the improvement of machinability by using different additional support, such
as the use of cryogenic cooling condition. Considering huge industrial demand of Mg alloy, and
its extensive processing via turning operation, the authors find it appropriate to study the
machining of AZ31B under different cooling and lubrication condition. Besides the conventional
approach of cutting conditions, the author has implemented the Minimum Quantity Lubrication
(MQL) to evaluate the surface quality in terms of six different roughness parameters. Based on
the knowledge found in the literature reviews, there is scope of conducting experimental study in
turning operation of AZ31B Mg alloy regarding surface roughness parameters:
 Arithmetic mean of roughness parameter (Ra)
 Root mean square roughness (Rq)
 Average maximum height surface roughness (Rz)
 Maximum height of the profile (Rt)
 Maximum profile peak height (Rp)
 Maximum profile valley depth (Rv)
Therefore, the objectives of the present research work are to-
 Study of different surface roughness parameters in turning of AZ31B Mg
 Determine the influence of dry, flood and MQL on roughness parameters
 Evaluate the influence of cutting speed, feed rate and depth of cut on the surface
roughness parameters

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Chapter 3
Methodology
3.1 Material: The work material expected to study is the commercial AZ31B magnesium
alloy. Magnesium alloy is a free-machining material. High cutting speed can be achieved to
increase the productivity of components in industry. However, the high cutting speed may induce
higher cutting temperature or can lead to chip ignition. Therefore, it is important to explore the
influence of the cutting temperature on the machining process of magnesium alloy.
The following table shows the physical properties, chemical composition, mechanical properties
and thermal properties of magnesium AZ31B alloy:
Table 3.1.1: Physical Properties
Properties Metric Imperial
Density 1.77 g/cm3 0.0639 lb/in³

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Table 3.1.2: Chemical Composition
Element Content (%)
Magnesium, Mg 97
Aluminium, Al 2.50-3.50
Zinc, Zn 0.60-1.40
Manganese, Mn 0.20
Silicon, Si 0.10
Copper, Cu 0.050
Calcium, Ca 0.040
Iron, Fe 0.0050
Nickel, Ni 0.0050
Table 3.1.3: Thermal Properties
Thermal expansion co-efficient (0-100°C/32-
212°F)
26 µm/m°C 14.4 µin/in°F
Thermal Conductivity 96 W/mK 666 BTU in/hr.ft².°F

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Table 3.1.4: Mechanical Properties
Tensile Strength 260 MPa 37700psi
Yield strength (strain 0.200%) 200 MPa 29000psi
Compressive Yield Strength(at 0.2% offset) 97 MPa 14100psi
Ultimate Bearing strength 385 MPa 55800psi
Bearing yield strength 230 MPa 33400 psi
Shear strength 130 MPa 18900 psi
Shear Modulus 17GPa 2470ksi
Elastic modulus 44.8 GPa 6498 ksi
Poissons Ratio 0.35 0.35
Elongation at break (in 50 mm) 15% 15%
Hardness, Brinell (500 kg load,10mm ball) 49 49
Charpy Impact (V-notch) 4.30 J 3.17 ft-lb
3.2 Machine: Cutting operation was conducted mainly on Engine Lathe Machine, Model:
CS6266B powered by a 7.5KW motor with a maximum spindle speed of 1600 rpm. The
specifications of the machine are given in Table-5 and its picture in Figure-2.

27 | P a g e
Fig. 3.2: Lathe Machine
Table 3.2.1: Specification of engine lathe of model CS6266B
Model CS6266B
Swing Over Bed 600 mm
Swing Over Cross Slide 420 mm
Maximum Length of The Workpiece 1000 mm
Speed Range 9-1600 rpm, 24 step
Maximum Output of The Spindle Range 1500 nm
Motor Speed 1450 rpm
3.3 Tool Holder: In the experiment a custom made cast iron tool holder was used. Its
dimension is 149x24x24 mm. The picture of the tool holder is shown in the Fig. 3 below.

28 | P a g e
Fig. 3.3: Tool holder
3.4 Insert: Coated tungsten carbide (WC) insert (Fig. 4) will be used for turning operation on
magnesium alloy AZ31B to investigate the machinability including surface roughness, cutting
force, cutting temperature, tool wear, tool life & chip morphology. The dimension of the insert is
12x12x5 mm.
Fig. 3.4: Coated carbide insert.

29 | P a g e
3.5 Workpiece: The workpiece will be used for the machinability investigation is
magnesium alloy AZ31B and the picture of the workpiece is shown in Fig.5. The workpiece is
50 cm long and its diameter is 7 cm.
Fig. 3.5: Magnesium alloy AZ31B workpiece
3.6 Experimental Setup: The Fig.6 is showing the experimental setup of the single point
cutting tool. The tool is secured in the machine. The cutting tool feeds into the rotating
workpiece and cuts away material in the form of small chips to create the desired shape.
Fig. 3.6: Machine tool setup.

30 | P a g e
3.7 Surface roughness measurement machine: The equipment used to measure the surface
roughness was a contact type Phase II SRG-4500. In the following Fig. 8 it is shown:
Fig. 3.7: Surface roughness tester.
Table 3.7.1: Specification of Phase II SRG-4500 surface roughness tester as follows:
Model SRG-4500 (phase II)
Catalog Model T-54103-06
Accuracy level .001μm
Surface roughness scale range 15
Contact type surface testers are capable of long distance measurement. The Phase II SRG-4500
surface roughness tester provides a high level of accuracy as the stylus moves closely with the
sample surface, so data is highly reliable.
Turning operation of Magnesium alloy AZ31Bwill be performed on Engine Lathe Machine. It
will be performed in different parameters and conditions. Surface roughness, cutting force,
cutting temperature, tool wear and tool life, chip morphology will be investigated.

31 | P a g e
Chapter 4
Results and discussion
4.1 Average surface roughness parameter, Ra
Fig. 4.1.1 shows the behavior of means of arithmetic mean surface roughness parameter with
respect to the variation of cutting speed, feed rate, depth of cut and cutting conditions. Here, the
cutting speed is varied between 45 m/min to 165 m/min, then the feed rate is changed from 0.10
mm/rev to 0.18 mm/rev, the cutting depth is taken from 0.5 mm to 1.5 mm. Lastly, the cutting
conditions which are practiced are the dry condition, the conventional flood cooling condition,
and the minimum quantity lubrication condition.
Fig. 4.1.1: Main effects plot for the arithmetic mean of roughness parameter (Ra). Here, the unit
of Ra is µm.
It is visible from Fig. 4.1.1 that the mean of Ra is insignificantly affected by the changes in the
cutting speed. This is evident, when the cutting speed is changed from the 45 m/min to 105

32 | P a g e
m/min; the mean of Ra is increased approximately by 0.10 µm. Contrary to this increase, a
further increment of cutting to 165 m/min, the mean of Ra is decreased by a small amount.
However, it is conclusive that the increase in cutting speed from the lowest to highest value
results in a slight increase in the mean of Ra.
Next to the cutting speed, the influence of feed rate is highly appreciable. As such, the increase
in feed rate from the lowest to the highest value has caused the mean of Ra to increase
drastically. To be specific, when the feed is moved up from 0.1 mm/rev to 0.14 mm/rev, the
mean of Ra showed a rapid increase by a magnitude of 0.5 µm (approximately). In proportionate,
the mean of Ra further increased by almost same amount when the feed rate is increased from
0.14 mm/rev to 0.18 mm/rev. If compared to the influence exerted by the cutting speed, the feed
rate has exhibited a far more dominant role in influencing the Ra.
Then, the criterion of cutting depth is considerable. Here it can be seen that the mean of
arithmetic means of roughness is marginally altered by slight increase of cutting depth. Here it’s
noticeable that, when the cutting depth is increased to 1.00 mm from 0.5 mm, a minor change in
the mean of Ra is identified which is almost 0.05 µm. Repeatedly when the depth of cut is
changed to 1.5 mm, the mean of Ra has changed around 0.05 µm. Nonetheless, it’s clear from
Fig. 4.1.1 that the increase of cutting depth from the smallest to highest value results in a slight
continuous inflation in the mean of Ra.
From the main effect plot shown in the Fig. 4.1.1, alteration in cutting condition and its effect on
the mean of Ra is clearly be seen. Here the changes of cutting condition from dry to conventional
flood condition and then to minimum quantity lubrication condition has caused the mean of Ra to
decrease gradually. When the condition changes from dry to flood condition the downward
change in the mean of Ra is calculated approximately as 0.12 µm. Similarly when cutting

33 | P a g e
condition was altered to minimum quantity lubrication, the mean of Ra got decreased by a margin
of 0.08 µm. In comparison to the impact shown by the depth of cut, cutting condition has
displayed reverse but similarly continuous changes in influencing the mean of Ra.
The response table used in Taguchi analysis is to determine the relative effects of control factors
on the response. For instance, Table 4.1.1 shows the response table for the average surface
roughness (Ra) with respect to four control factors such as cutting speed, feed rate, depth of cut
and cutting condition. Here, the mean of the mean surface roughness is computed corresponding
to each level of the mentioned factors. The factor with the highest value of delta is taken as the
highest contributing factor. Note that ‘delta’ is defined the difference between the ‘maximum’
and ‘minimum’ value of the mean of all levels for that particular factor. As an example, shown in
Table 4.1.1, we can see that the feed rate has the highest value of delta = 0.9059; therefore, feed
rate is the most dominant factor among all four factors. As the delta value for cutting condition is
second in magnitude, it is the second most significant factor. Likewise, the depth of cut is third in
rank and the cutting speed has the least effect on the average surface roughness value.
Table 4.1.1
Response Table for mean of means of average surface roughness (Ra). [Smaller
is better]
Level Cutting speed Feed rate Depth of cut Cutting condition
1 1.0679 0.6410 1.0605 1.1867
2 1.1194 1.1119 1.1019 1.0799
3 1.1125 1.5469 1.1375 1.0332
Delta 0.0515 0.9059 0.0770 0.1536
Rank 4 1 3 2
Fig. 4.1.2 exhibits the contour plot of average surface roughness parameter (Ra) with respect to
feed rate and depth of cut. Here, in developing the contour plot, the two control factors with the

34 | P a g e
highest ranking i.e. feed rate and depth of cut, found from the response table that was generated
by Taguchi method, are used as the axis variable. In this figure, each color band represents a
width of roughness value.
Fig. 4.1.2: Contour plot of Ra vs feed and depth of cut. Here, the unit of Ra is µm, feed is mm/rev,
and depth of cut is mm.
It is noticeable that with the variation of the depth of cut, the band of average surface roughness
value hardly changes. However, due to the variation of feed rate, the Ra changes by creating
different color band. As such, the lower feed rate is associated with lower surface roughness and
vice versa. This relation is irrespective of the changes made in depth of cut.
Fig. 4.1.3 presents the surface plot of average surface roughness (Ra) with respect to depth of cut
and feed rate. In establishing the surface plot, the two major factors with the highest importance
i.e. depth of cut and feed rate, found from the response table which achieved from Taguchi
method, are used as axis variables. And in Z-axis the values of average surface roughness (Ra)
are represented.
Depth of Cut
Feed
1.501.251.000.750.50
0.175
0.150
0.125
0.100
>
–
–
–
–
–
< 0.50
0.50 0.75
0.75 1.00
1.00 1.25
1.25 1.50
1.50 1.75
1.75
Ra
Contour Plot of Ra vs Feed, Depth of Cut

35 | P a g e
From this figure when depth of cut is increasing, the value of Ra is increasing in minor contrast.
On the other hand, when the feed rate is increasing the value of Ra is increasing in a more
noticeable drastic manner. Here in this surface plot the waviness occurred at some places due to
the interaction between feed and depth of cut.
Fig. 4.1.3: Surface Plot of Ra vs Feed, Depth of Cut. Here, the unit of Ra is µm, feed is mm/rev,
4.2 Root mean square roughness parameter (Rq)
Fig. 4.2.1 shows the nature of means the root mean square roughness parameter with respect to
the variation of cutting speed, feed rate, depth of cut and cutting conditions. Here, the cutting
speed is shifted between 45 m/min to 165 m/min, then the feed rate is changed from 0.10 mm/rev
to 0.18 mm/rev, the cutting depth is taken from 0.5 mm to 1.5 mm. Finally, the cutting
conditions which were operated are the dry condition, the conventional flood cooling condition,
and the minimum quantity lubrication condition.
5.0
0.1
.0 5
1.0
51.
0 521.
0.100
5.1
0
00.15
0 521.
0.175
51.
0.2
aR
deeF
tuCfohtpeD
urfS ce Plot of Ra vs Feed, Cutting Speeda

36 | P a g e
Fig. 4.2.1: Main effects plot for the root mean square roughness (Rq). Here, the unit of Rq is µm.
It is detectable from Fig. 4.2.1 that the mean of Rq is less significantly affected by the changes in
the cutting speed. This is seen that, when the cutting speed is geared up from the 45 m/min to
105 m/min; the mean of Rq is increased approximately by 0.07 µm. Adverse to this increase, a
further increase in cutting speed to 165 m/min, the mean of Ra is decreased by a small content.
However, it is decisive that the rise in cutting speed from the lowest to highest value results in a
slight escalation in the mean of Rq.
After the cutting speed, the significance of feed rate is highly observable. It is clearly seen that,
the increase in feed rate from the lowest to the highest value has caused the mean of Rq to
increase exceedingly. To be definite, when the feed is boosted up from 0.1 mm/rev to 0.14
mm/rev, the mean of Rq showed an accelerated-up rise by an approximate degree of 0.5 µm.
Again, the mean of Rq further increased by almost 0.5 µm when the feed rate is increased from
0.14 mm/rev to 0.18 mm/rev. This variation in feed differs from the variation seen in cutting
speed, both resulting in increased amount of mean of Rq.

37 | P a g e
From the plot of cutting depth it can be seen that the root mean square of surface roughness is
somewhat altered by slight increase of cutting depth. It’s visible that, when the cutting depth is
increased to 1.00 mm from 0.5 mm, a bit of change in the mean of Rq is identified which is
almost 0.05 µm. Repeatedly when the depth of cut is changed to 1.5 mm, the mean of Rq has
increased around 0.05 µm from the previous increase. It’s clear from Fig. 4.2.1 that the increase
of cutting depth from the lowest to highest value results in a slight continuous hike in the mean
of Rq.
From the graphical main effect plot of shown in the Fig. 4.2.1, change in cutting condition and
its effect on the mean of Rq is noticeable. When the cutting condition is changed from dry to
flood condition, the mean of Rq decreased continuously. And the amount of change in Rq is
approximately 0.14 µm. Again when the condition changes from flood to minimum quantity
lubrication condition the descending change in the mean of Rq is calculated approximately 0.07
µm. In comparison with the impact shown by the depth of cut, cutting condition has shown
contradictory but regular changes in manipulating the mean of Rq.
The response table used in Taguchi analysis is to determine the relative effects of control factors.
For example, Table 4.2.1 presents the response table for the root mean square roughness (Rq)with
respect to four control factors such as cutting speed, feed rate, depth of cut and cutting condition.
Here, the mean of the mean surface roughness is calculated comparable to each level of the
stated factors. The factor with the maximum value of delta is taken as the highest contributing
factor. Here ‘delta’ is described by the difference between the ‘maximum’ and ‘minimum’ value
of the mean of all levels for that appropriate factor. From the above Table 2, it is identified that
the feed rate has the highest value of delta = 1.0385; therefore, feed rate is the most prevailing
factor among all four factors. As the delta value for cutting condition is second in significance, it

38 | P a g e
is the second most dominant factor. Besides, the depth of cut resides in third rank and the cutting
speed has the minimum effect on the value of root mean square roughness.
Table 4.2.1
Response Table for mean of means of root mean square roughness (Rq) [Smaller
is better]
1 1.2626 0.7876 1.2551 1.4190
2 1.3328 1.3080 1.3110 1.2869
3 1.3264 1.8261 1.3556 1.2159
Delta 0.0702 1.0385 0.1005 0.2031
Rank 4 1 3 2
Fig. 4.2.2 displays the contour plot of root mean square roughness (Rq) with relation to feed rate
and depth of cut. Here, in creating the contour plot, the two control factors with the highest
ranking i.e. feed rate and depth of cut, originated from the response table that was generated by
Taguchi method, are used as the axis variable. In this figure, every color band illustrates a
breadth of mean square roughness value.

39 | P a g e
Fig. 4.2.2: Contour Plot of Rq vs Feed, Cutting Speed. Here, the unit of Rq is µm, feed is mm/rev,
It is evident that with the dissimilarity of the depth of cut, the band of root mean square
roughness value barely differs. Nevertheless, due to the deviation of feed rate, the Rq varies by
creating different color band. For instance, the lower feed rate is related with lower surface
roughness and vice versa. This relation is impartial of the changes made in depth of cut.
Fig. 4.2.3 displays the surface plot of root mean square roughness (Rq) corresponding to depth of
cut and feed rate. While generating the surface plot, the two control factors with the highest
importance i.e. depth of cut and feed rate, found from the response table which achieved from
Taguchi method, are used as axis variables. And in Z-axis the values of root mean square
roughness (Rq) are represented.
Depth of Cut
Feed
1.501.251.000.750.50
0.175
0.150
0.125
0.100
>
–
–
–
–
–
< 0.6
0.6 0.9
0.9 1.2
1.2 1.5
1.5 1.8
1.8 2.1
2.1
Rq
Contour Plot of Rq vs Feed, Depth of Cut

40 | P a g e
Fig. 4.2.3: Surface Plot of Rq vs Feed, Depth of Cut. Here, the unit of Rq is µm, feed is
mm/rev, and depth of cut is mm.
From this surface plot it is evident that when depth of cut is incrementing, the value of Rq is
increasing in small content. But the value of Rq is increasing exceedingly when the feed rate is
escalated. Here in this surface plot at some points waviness can be seen. Here in this surface plot
at some points waviness can be seen. It is occurred due to the interaction between feed and depth
of cut.
4.3 Average maximum height surface roughness
Fig. 4.3.1 explains that the mean of Rz is affected by the changes in the cutting speed. This is
seen that, when the cutting speed is increased from the 45 m/min to 105 m/min; the mean of Rzis
increased relatively by 0.18 µm. Conflicting to this increase, a further increase in cutting speed
to 165 m/min, the mean of Rz is decreased by a small breadth. However, it is decisive that the rise
in cutting speed from the lowest to highest value results in a slight boost in the mean of Rz.
0.5
1.0
.0 5
1 0.
.1 5
10. 52
001.0
5.1
0
.10 50
10. 52
.170 5
2.0
qR
deeF
tuCfohtpeD
urface Plot of Rq v Feed, Depth ofS Cuts

41 | P a g e
After the cutting speed, the implication of feed rate is highly detectable. It is clear-cut visible
that, the increase in feed rate from the lowest to the highest value has caused the mean of Rz to
increase enormously. To be categorical, when the feed is boosted up from 0.1 mm/rev to 0.14
mm/rev, the mean of Rz showed an accelerated increase by an approximate degree of 1.55 µm.
Again the mean of Rz further increased by almost 1.05 µm when the feed rate is increased from
0.14 mm/rev to 0.18 mm/rev. Now if these changes in feed rate are compared to the changes in
cutting speed, then both of them has considerable influence in increasing the value of mean of Rz.
Fig. 4.3.1: Main effects plot for the ten-point mean roughness (Rz). Here, the unit of Rz is µm.
From the cutting depth portion of the graph it can be seen that the mean of Rz is fairly modified
by minor increases of cutting depth. It’s noticeable that, when the cutting depth is increased to
1.00 mm, a change in the mean of Rz is identified which is almost 0.32 µm. Again the mean of Rz
has increased around 0.23 µm when the depth of cut is changed to 1.5 mm. Nonetheless, with the
development of the cutting depth, the mean of Rz increases at a continual rate.

42 | P a g e
The main effect plot for the ten-point mean roughness shown in the Fig. 4.3.1 presents change in
cutting condition and its effect on the mean of Rz. During the change of cutting condition from
dry to flood condition, the mean of Rz is suddenly decreased to an approximate amount of 0.40
µm. Similarly when the cutting condition changes from flood to MQL condition, the descending
change in the mean of Rz is calculated approximately 0.20 µm. In comparison with the impact
shown by the depth of cut, cutting condition has shown contradictory but regular changes in
manipulating the mean of Rz.
The response table is exercised in Taguchi analysis to determine the corresponding effects of
input factors on the response. For this case, the response table for the average maximum height
(Rz) is shown in Table 4.3.1 with respect to four control factors such as cutting speed, feed rate,
cutting depth and cooling methods. Here, corresponding to every level of the mentioned factors
the mean of the mean average maximum height is computed. The factor with the highest delta
value is considered as the highest contributing factor for the above particular roughness
parameter. The difference between the ‘maximum’ and ‘minimum’ value of the mean of all
levels for that particular factor is the value of ‘delta’. As shown in Table 3, we can see that the
feed rate scores the highest value of d1elta = 2.812; therefore, feed rate is the most dominant
factor among all the other four input variables. The delta value for cutting condition is second in
magnitude scoring 0.838, so it is the second most significant factor. And then, the depth of cut
scoring 0.612 is third in rank and the cutting speed has the least effect on the average maximum
height value.

43 | P a g e
Table 4.3.1
Response Table for mean of means of average maximum height (Rz). [Smaller is
better]
1 4.412 2.980 4.215 5.019
2 4.536 4.831 4.561 4.402
3 4.655 5.792 4.827 4.182
Delta 0.243 2.812 0.612 0.838
Rank 4 1 3 2
The contour plot of average maximum height (Rz) with respect to feed rate and depth of cut is
shown in Fig. 4.3.2 Here, Taguchi method is used to develop the axis variables of the contour
plot, the two control factors with the highest position i.e. feed rate and depth of cut, found from
the response table was generated by Taguchi method. Each color band describes a range of
average maximum height values.
Fig. 4.3.2: Contour Plot of Rzvs Feed, Depth of Cut. Here, the unit of Rz is µm, feed is mm/rev,
Depth of Cut
Feed
1.501.251.000.750.50
0.175
0.150
0.125
0.100
–
–
–
–
–
< 2
2 3
3 4
4 5
5 6
6 7
Rz
Contour Plot of Rz vs Feed, Depth of Cut

44 | P a g e
It is conspicuous that with the discrepancy of the depth of cut, the band of average maximum
heightvalue scarcely changes for all color bands except the red zone which changes after 0.80
mm approximately. On the other hand, due to the disparity of feed rate, the Rz changes by
creating different color band. For example, the lower feed rate is connected with lower surface
roughness and vice versa. This relation does not depend on the variations made in depth of cut.
Fig. 4.3.3 exhibits the surface plot of average maximum height (Rz) related to feed rate and depth
of cut. Here, in developing the contour plot, the two control factors with the highest ranking i.e.
feed rate and depth of cut, found from the response table that was generated by Taguchi method,
are used as the axis variable. And in Z-axis the values of average surface roughness (Rz) are
represented.
Fig. 4.3.3: Surface Plot of Rzvs Feed, Depth of Cut. Here, the unit of Rz is µm, feed is mm/rev,
From the above figure it is clearly visible that when depth of cut is increasing, the value of Rzis
increasing slightly. Yet when the feed rate is increasing the value of Rz is increasing greatly.Here
the waviness createdat some points is due to the interaction between feed and depth of cut.
0.5
1.0
2
4
6
1. 50 2
0.100
5.1
0
. 00 51
1. 50 2
0.175
6
8
zR
deeF
tuCfohtpeD
urface Plot ofS Rz v Feed, Depth of Cuts

45 | P a g e
4.4 Maximum height of the surface parameter (Rt)
Here Fig. 4.4.1 shows the nature of the maximum height of the profile with respect to the
variation of cutting speed, feed rate, depth of cut and cutting conditions. Here, the cutting speed
is shifted between 45 m/min to 165 m/min, then the feed rate is changed from 0.10 mm/rev to
0.18 mm/rev, the cutting depth is taken from 0.5 mm to 1.5 mm. Finally, the cutting conditions
which were operated are the dry condition, the conventional flood cooling condition, and the
minimum quantity lubrication condition.
Fig. 4.4.1: Main effects plot for the maximum height of the profile (Rt). Here, the unit of Rt is
µm.
It is noticeable from Fig. 4.4.1that the mean of Rtis kind of affected by the alterations in the
cutting speed. This is seen that, when the cutting speed is geared up from the 45 m/min to 105
m/min; the mean of Rtis slightly increased by approximately 0.20 µm. Adverse to this increase, a
further escalation in cutting speed to 165 m/min; the mean of Rtis decreased by a small content.
However, it is decisive that the rise in cutting speed from the lowest to highest value results in a
slight escalation in the mean of Rt.

46 | P a g e
After the cutting speed, the significance of feed rate is highly observable. It is clearly seen that,
the increase in feed rate from the lowest to the highest value has caused the mean of Rt to
increase exceedingly. To be definite, when the feed rate is boosted up from 0.1 mm/rev to 0.14
mm/rev, the mean of Rt showed an accelerated up rise by an approximate degree of 2.05 µm.
Again the mean of Rt is further increased by almost 1.65 µm when the feed rate is increased from
0.14 mm/rev to 0.18 mm/rev. This variation in feed differs from the variation seen in cutting
speed, both resulting in increased amount of mean of Rt.
From the cutting depth portion it can be seen that the mean of Rtis somewhat changed by slight
increase of depth of cutting. It’s visible that, when the cutting depth is increased to 1.00 mm
from 0.5 mm, slight change in the mean of Rt is identified which is almost 0.05 µm. Similarly
when the depth of cut is changed to 1.5 mm from 1 mm, the mean of Rt has increased almost 0.4
µm in comparison with the previous increase. It’s clear from Fig. 4.4.1 that the increase of
cutting depth from the lowest to highest value results in a slight continuous increase in the mean
of Rt.
From the main effect plot of shown in the Fig. 4.4.1, changes in cutting condition and its effect
on the mean of Rt is noticeable. When the cutting condition is changed from dry to flood
condition, the mean of Rt decreases frequently. The amount is approximately 1.9 µm. Again
when the condition changes from conventional flood to minimum quantity lubrication condition
the descending change in the mean of Rt is calculated approximately 0.20 µm. In comparison
with the impact shown by the depth of cut, cutting condition has shown contradictory but regular
changes in manipulating the mean of Rt.
The response table is used in Taguchi analysis to determine the corresponding effects of control
factors on the response. Here, Table 4.4.1 represents the response table for the maximum height

47 | P a g e
of the surface (Rt) with respect to four control factors such as cutting speed, feed rate, depth of
cut and cutting condition. The mean of the mean surface roughness is computed by Taguchi
method in parallel to each level of the mentioned factors. The factor scoring the highest value of
delta is taken as the highest contributing factor. The term ‘delta’ is defined by difference between
the ‘maximum’ and ‘minimum’ value of the mean of all levels for that exact factor. For example,
as shown in Table 4.4.1, it is evident that the feed rate has the highest value of delta = 3.719;
that’s why feed rate is the most dominant factor among all the other four factors. As the delta
value for cutting condition is second in rank scoring 1.162, it is the second most significant
factor. In the same way, the depth of cut is third in rank scoring 0.835 and the cutting speed has
the least effect on the average surface roughness value.
Table 4.4.1
Response Table for mean of means of the maximum height of the surface (Rt)
[Smaller is better]
1 6.035 4.141 5.657 6.758
2 6.173 6.221 6.075 5.869
3 6.014 7.860 6.491 5.596
Delta 0.160 3.719 0.835 1.162
Rank 4 1 3 2
The contour plot of maximum height of the surface roughness (Rt) with respect to feed rate and
depth of cut is shown in Fig. 4.4.2. Here, the two control factors with the highest position i.e.
feed rate and depth of cut, found from the response table that was generated by Taguchi method,
are used as the axis variables. All color bands display a boundary of maximum height of the
surface roughness.
It is prominent that with the increase of the depth of cut, the band of average maximum
heightvalue does not quite change for all color bands except the red and purple zone which is

48 | P a g e
lowest value Rtand the highest level of color band respectively. Then again, due to the difference
of feed rate, the Rt changes by creating diverse color band. For example, the lower feed rate is
connected with low surface roughness and vice versa. This relation does not depend on the
variations made in depth of cut.
Fig. 4.4.2: Contour Plot of Rtvs Feed, Depth of Cut. Here, the unit of Rt is µm, feed is mm/rev,
Fig. 4.4.3 presents the surface plot of the maximum height of the surface (Rt) with respect to
depth of cut and feed rate. In establishing the surface plot, the two major factors with the highest
Taguchi method, are used as axis variables. And in Z-axis the values of average surface
roughness (Rt) are represented.
Depth of Cut
Feed
1.501.251.000.750.50
0.175
0.150
0.125
0.100
>
–
–
–
–
–
–
< 3
3 4
4 5
5 6
6 7
7 8
8 9
9
Rt
Contour Plot of Rt vs Feed, Depth of Cut

49 | P a g e
Fig. 4.4.3: Surface Plot of Rtvs Feed, Depth of Cut. Here, the unit of Rt is µm, feed is mm/rev,
From this figure it can be seen that when depth of cut is increasing, the value of Rt is increasing
in a smaller extent maintaining a wavy manner. But when the feed rate is increasing the value of
Rt is increasing in a more observable drastic manner. Here in this surface plot the waviness
occurred at some places due to the interaction between feed and depth of cut.
4.5 Maximum profile peak height (Rp)
Fig. 4.5.1 shows the characteristics of the maximum profile peak height (Rp) with respect to the
variation of cutting speed, feed rate, depth of cut and cutting conditions. In this figure the mean
of Rpis fractionally affected by the changes in the cutting speed. Conspicuously when the cutting
speed switches from 45 m/min to 105 m/min, the mean of Rp is increased approximately by 0.21
µm. After that, an increment of cutting speed to 165 m/min from 105 m/min causes the mean of
Rpto increase in very inconsiderable amount. But no matter how smaller fractional variation in
.0 5
.01
4
6
8
. 5210
01.0 0
5.1
0
501.0
. 5210
51.0 7
8
10
tR
deeF
tuCfohtpeD
urface Plot oS Rt vf Feed, Depth of Cuts

50 | P a g e
the mean of Rp has it is still quite evident that the increase in cutting speed from the lowest to
highest value results in a slight increase in the mean of Rp.
Fig. 4.5.1: Main effects plot for the maximum profile peak height (Rp). Here, the unit of Rp is
µm.
Subsequently after the cutting speed, the influence of feed rate is exceptionally remarkable. The
rise in feed rate from the lowest to the highest value has clearly caused the mean of Rpto increase
exorbitantly. To be more accurate, when the feed is passed from 0.1 mm/rev to 0.14 mm/rev, the
mean of Rp asserted a rapid increase to some extent of 1.2 µm approximately. Similarly, the
mean of Rptherewithal ascended by nearly an equal quantity when the feed rate changed from
0.14 mm/rev to 0.18 mm/rev. In comparison, the feed rate displayed much more influence on
changing the mean of Rp than the cutting speed has exhibited.
Followed by the feed rate in comes the cutting depth which shows that the mean of maximum
profile peak height shifts from 0.5 mm to 1.0 mm and creates an increasing variation of around
0.41µm. Likewise when the depth of cut is moved to 1.5 mm from 1.0 mm, the mean of Rp has

51 | P a g e
moved in the region of 0.22 µm approximately. In spite of that it is noticeable from Fig. 4.5.1
that the increase in cutting depth from the lower to upper value results in a gradual increment in
the mean of Rp.
Finally in cutting condition changes in the mean of Rp is detectable from Fig. 4.5.1. Here the
changes of cutting condition from dry to conventional flood condition and then to minimum
quantity lubrication condition has caused the mean of Rp to gradually decrease. When the
condition changes from dry to flood condition the descending change in the mean of Rpwas
calculated approximately 0.4 µm. When the cutting condition was progressed to minimum
quantity lubrication, the mean of Rp got lessened by a margin of 0.02 µm. In comparison with the
impact shown by the depth of cut, cutting condition has displayed contrary but similarly
continuous changes in swaying the mean of Rp.
The response table is used in Taguchi analysis to determine the resultant effects of control
factors on the response. For instance, Table 4.5.1 shows the response table for the maximum
profile peak height (Rp) regarding four control factors such as cutting speed, feed rate, cutting
depth cut and cooling methods. Here, the mean of the mean of maximum profile peak height is
computed corresponding to each level of the mentioned factors. The factor with the highest value
of delta is taken as the highest contributing factor. Note that ‘delta’ is defined the difference
between the ‘maximum’ and ‘minimum’ value of the mean of all levels for that particular factor.
From the data shown in Table 4.5.1, we can see that the feed rate has the highest value of delta =
2.086; therefore, feed rate is the most leading factor among all the other four input factors. As the
delta value for cutting depth is second in magnitude, it is the second most significant factor.
Likewise, the cutting condition is third in rank. And then the cutting speed which is last in rank

52 | P a g e
confirming from the response table has the least effect on the value of the maximum profile peak
height (Rp).
Table 4.5.1
Response Table for mean of means of the maximum profile peak height (Rp).
[Smaller is better]
1 2.597 1.641 2.375 3.020
2 2.807 2.861 2.787 2.611
3 2.825 3.727 3.068 2.598
Delta 0.228 2.086 0.693 0.422
Rank 4 1 2 3
The contour plot of maximum profile peak height (Rp) with respect to feed rate and depth of cut
is shown in Fig. 4.5.2. Here, the two control factors with the highest position i.e. feed rate and
depth of cut, found from the rank of the response table, was generated by Taguchi method, are
used as the axis variable. All color bands display a boundary of maximum height of the surface.
Fig. 4.5.2: Contour Plot of Rpvs Feed, Depth of Cut. Here, the unit of Rp is µm, feed is
mm/rev, and depth of cut is mm.
Depth of Cut
Feed
1.501.251.000.750.50
0.175
0.150
0.125
0.100
>
–
–
–
–
< 1
1 2
2 3
3 4
4 5
5
Rp
Contour Plot of Rp vs Feed, Depth of Cut

53 | P a g e
From Fig. 4.5.2 it is prominent that with the escalation of the depth of cut, the band of average
maximum height value not quite changes for all color bands except the purple zone. That is the
highest value of Rp. Then again, due to the difference of feed rate, the Rp changes by creating
different color band. For instance, the lower feed rate represents lower maximum profile peak
height (Rp) and vice versa. This relation does not rely on the variations made in depth of cut.
Fig. 4.5.3 represents the surface plot for the maximum profile peak height (Rp) with respect to
depth of cut and feed rate. In establishing the surface plot, the two major factors with the highest
Taguchi method, are used as axis variables. And in Z-axis the values of average surface
roughness (Rp) are represented.
From this figure it can be seen that when depth of cut is increasing, the value of Rp is increasing
in minor contrast. But when the feed rate is increasing the value of Rp is increasing too. Here in
this surface plot the waviness occurred at some places due to the interaction between feed and
depth of cut.
Fig. 4.5.3: Surface Plot of Rpvs Feed, Depth of Cut. Here, the unit of Rp is µm, feed is mm/rev,
50.
1.0
1.0
52.
4.0
52.10
000 1.
5.1
0
0 051.
52.10
570.1
4.0
5 5.
pR
deeF
tuCfohtpeD
urface Plot of Rp v dFeeS , Depth of Cuts

54 | P a g e
4.6 Maximum profile valley depth (Rv)
Here Fig. 4.6.1 shows the sign of the means of maximum profile valley depth (Rv) with respect to
the variation of cutting speed, feed rate, depth of cut and cutting conditions. It is visible from
Fig. 4.6.1 that the changes in the mean of Rvis very little and negligible which is caused by the
cutting speed. Variation from the 45 m/min to 105 m/min in cutting speed causes the mean of Rv
to increase around 0.07 µm. After further increment of cutting speed to 165 m/min, the mean of
Rv is decreased by a fractional amount. Nevertheless, it is certain that the increase in cutting
speed from the lowest to highest value results in a slight increase in the mean of Rv.
Fig. 4.6.1: Main effects plot for the maximum profile valley depth (Rv). Here, the unit of Rv is
µm.
The impact of feed rate is highly palpable. Intrinsically the increase in feed rate from the lowest
to the highest value has initiated the mean of Rv to escalate extremely. Precisely the feed is
moved up from 0.1 mm/rev to 0.14 mm/rev, the mean of Rv showed a quick upturn by an amount
of 0.5 µm (approximately). The mean of Rv further improved but in a much less amount when

55 | P a g e
the feed rate is moved from 0.14 mm/rev to 0.18 mm/rev. The feed rate has demonstrated a far
more leading role than cutting speed in manipulating the mean of Rv.
Apparently the cutting depth section shows that the mean of maximum profile valley depths
wings from 0.5 mm to 1.0 mm and creates a minor downward variation of around 0.07µm.
Similarly when the depth of cut is progressed to 1.5 mm from 1.0 mm, the mean of Rv has faintly
decreased just about 0.03µm. Despite of that it is visible from Fig. 4.6.1 that the increase in
cutting depth from the lesser to higher value results in a continuing decrement in the mean of Rv.
Lastly in cutting condition, fluctuations in the mean of Rv is obvious from Fig. 4.6.1. The
deviations of cutting condition from dry to conventional flood condition and then to minimum
quantity lubrication condition has caused the mean of Rv to slowly but surely decline. When the
condition varies from dry to flood condition the plunging change in the mean of Rvwas calculated
approximately 0.2 µm. As such when the cutting condition was advanced to minimum quantity
lubrication, the mean of Rv got decreased by a margin of 0.04 µm. Comparatively the cutting
condition has revealed more opposite but also nonstop changes than the depth of cut in
influencing the mean of Rv.
The response table is used in Taguchi analysis to determine the relative effects of control factors
on the response. For instance, Table 4.6.1 shows the response table for the maximum profile
valley depth (Rv)relating to four control factors such as cutting speed, feed rate, depth of cut and
cutting condition. Here, the mean of the mean maximum profile valley depth is computed
relative to each level of the mentioned factors. The factor with the highest value of delta is taken
as the highest contributing factor. From the above response table ‘delta’ is termed as the
difference amid the ‘greatest’ and ‘least’ value of the mean of all levels for that exact factor. For
example, given in Table 4.6.1, it is clearly seen that the feed rate has the highest value of delta =

56 | P a g e
0.865; hence, feed rate is the most governing factor among all four factors. Since the delta value
for cutting condition is second in rank scoring 0.244, it is the second most major factor.
Similarly, the cutting depth is third in rank and the cutting speed has the least effect on the
average surface roughness value.
Table 4.6.1
Response Table for mean of means the maximum profile valley depth (Rv).
[Smaller is better]
1 1.810 1.339 1.896 1.987
2 1.876 1.970 1.824 1.784
3 1.828 2.205 1.795 1.743
Delta 0.067 0.865 0.101 0.244
Rank 4 1 3 2
Fig. 4.6.2 illustrates the contour plot of average surface roughness parameter (Rv) with respect to
feed rate and depth of cut. Here, in developing the contour plot, the two control factors with the
highest ranking i.e. feed rate and depth of cut, found from the response table that was generated
by Taguchi method, are used as the axis variable. In this contour plot, each color band specifies a
width of roughness value.

57 | P a g e
Fig. 4.6.2: Contour Plot of Rvvs Feed, Depth of Cut. Here, the unit of Rv is µm, feed is mm/rev,
It is visible that with the variation of the depth of cut, the band of maximum profile valley depth
value hardly changes. However, due to the variation of feed rate, the Rv changes by creating
different color band. As such, the lower feed rate is associated with lower surface roughness and
the upper portion of the plot represents higher values of Rv. This relation is irrespective of the
change made in depth of cut.
Fig. 4.6.3 displays the surface plot for the maximum profile valley depth (Rv) corresponding to
depth of cut and feed rate. While generating the surface plot, the two control factors with the
highest importance i.e. depth of cut and feed rate, found from the response table which achieved
from Taguchi method, are used as axis variables. And in Z-axis the values of root mean square
roughness (Rv) are represented.
Depth of Cut
Feed
1.501.251.000.750.50
0.175
0.150
0.125
0.100
>
–
–
–
–
< 1.0
1.0 1.5
1.5 2.0
2.0 2.5
2.5 3.0
3.0
Rv
Contour Plot of Rv vs Feed, Depth of Cut

58 | P a g e
From this surface plot it is evident that when depth of cut is incrementing, the value of Rv is
increasing in small content. But the value of Rv is increasing exceedingly when the feed rate is
escalated. Here in this surface plot at some points waviness can be seen. Here in this surface plot
at some points waviness can be seen. It is occurred due to the interaction between feed and depth
of cut.
Fig. 4.6.3: Surface Plot of Rvvs Feed, Depth of Cut. Here, the unit of Rv is µm, feed is mm/rev,
50.
1.0
1
2
0.125
0.10 0
5.1
0
051.0
0.125
571.0
3
vR
deeF
tuCfohtpeD
urface Plot of Rv v dFeeS , Depth of Cuts

59 | P a g e
Chapter 5
Conclusion
A study comprising of different surface roughness parameters of AZ31B Mg alloy was done in
this experiment successfully. The study was done by turning AZ31B Mg alloy under varied feed,
depth and cooling condition i.e., dry, conventional flood, MQL. Different amount of surface
roughness was measured by the service of a roughness tester. The collected data from the turning
operation were used to analyze and get desirable results on behalf of low surface roughness. The
analysis was done by means of Taguchi method and the following results were shown:
 The experimentation shows that, the cutting speed has insignificant impact on the studied
surface roughness parameters.
 Feed rate has significant influence over the surface roughness parameters. It expressed
itself as the most dominant control factor to determine a better surface roughness
parameter.
 Depth of cut has insignificant influence over the surface roughness parameter and it has
less effect on the roughness parameters compared to feed rate.
 In cutting condition, MQL emerged as the major cooling condition compared to other two
conditions which are dry and flood condition.
The future study can be conducted on the investigation of tool wear and chip morphology in
turning of Mg AZ31B alloy under dry, flood and MQL conditions.

60 | P a g e
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