A. GÖK: 2D NUMERIC SIMULATION OF SERRATED-CHIP FORMATION IN ORTHOGONAL CUTTING OF AISI316H ...
953–956
2D NUMERIC SIMULATION OF SERRATED-CHIP FORMATION
IN ORTHOGONAL CUTTING OF AISI316H STAINLESS STEEL
NUMERI^NA 2D SIMULACIJA NASTANKA NAZOB^ANEGA
ODREZKA PRI PRAVOKOTNEM REZANJU AISI316H JEKLA
Arif Gök
Amasya University, Faculty of Technology, Department of Mechanical Engineering, 05100 Amasya, Turkey
arif.gok@amasya.edu.tr
Prejem rokopisa – received: 2017-04-06; sprejem za objavo – accepted for publication: 2017-05-30
doi:10.17222/mit.2017.038
Low thermal conductivity, high strength, high ductility and high work-hardening tendency of austenitic stainless steels are the
main factors that make their machinability difficult. This study investigates the influence of material modelling on the
serrated-chip formation during the orthogonal cutting of the AISI316H stainless steel using finite-element simulations. Turning
tests were carried out at three different cutting speeds and constant depth of cut and feed rate. Predictions were compared with
the orthogonal-cutting tests and found to be in agreement.
Keywords: AISI 304 stainless steel, finite-element method, serrated-chip formation, machinability
Nizka toplotna prevodnost, visoka trdnost, velika duktilnost in sposobnost mo~nega utrjevanja so glavni vzroki za to, da se
austenitno nerjavno jeklo te`ko mehansko obdeluje. V {tudiji so avtorji modelirali tvorbo nazob~anega ostru`ka med pravo-
kotnim rezanjem AISI316H nerjavnega jekla. Za modeliranje so uporabili metodo kon~nih elementov (MKE). Preizkusi
stru`enja so bili izvedeni pri treh razli~nih rezalnih hitrostih ter pri konstantni globini reza in pomikanja. Rezultate modeliranja
so primerjali s prakti~nimi preizkusi pravokotnega rezanja (stru`enja). Ugotovili so, da se prakti~ni rezultati preizkusov dobro
ujemajo z rezultati MKE-modeliranja.
Klju~ne besede: AISI 304 nerjavno jeklo, metoda kon~nih elementov, tvorba nazob~anih ostru`kov, sposobnost strojnega
obdelovanja
1 INTRODUCTION
Austenitic stainless steels, characterised by a high
work-hardening rate and low thermal conductivity 1, are
used to fabricate chemical and food-processing equip-
ment, as well as machinery parts requiring high corro-
sion resistance.2 They are generally regarded as more
difficult to machine than carbon and low-alloy steels on
account of their high strength, high work-hardening
tendency and poor thermal conductivity.3,4 Problems such
as poor surface finish and high tool wear are common.5
Work hardening is recognised to be responsible for the
poor machinability of austenitic stainless steels.6 In
addition, they bond very strongly to the cutting tool
during cutting and when a chip is broken away, it may
bring with it a fragment of the tool, particularly when
cutting with cemented carbide tools. When machining
this material, cutting-force variation is also much more
obvious than in the case of machining unalloyed steel.1
Especially, in order to increase the productivity and
tool life in the machining of the AISI304 and AISI316
series stainless steel, it is necessary to develop a reliable
FE model for different cutting processes. To accurately
analyse this process using numerical methods such as the
finite-element analysis (FEA), the knowledge of the
material constitutive behaviour under these severe load-
ing conditions is a pre-requisite and hence correct work-
material flow-stress data need to be used. In fact, the
success and reliability of numerical models are heavily
dependent upon the work-material-flow stress, friction
parameters for the tool and work-material interfaces, the
fracture criterion and thermal parameters.3,7–10
Many studies on the chip formation have been
published by now. Titanium alloys are used in most of
these studies. M. Bäker11 studied the influence of the
material law determining the plastic flow on the chip
formation of titanium alloys at high cutting speeds, while
T. Özel et al.12 studied constitutive-material models to
simulate the serrated-chip formation, including also
other materials. In parallel with these investigations,
M. Sima and T. Özel13 investigated the influence of con-
stitutive-material models and elastic/viscoplastic finite-
element formulation on a serrated-chip formation for
modelling the machining of the Ti–6Al–4V titanium
alloy. R. Alvarez et al.14 analysed the effect of eight
constitutive models on the saw-toothed chip formation in
Ti6Al4V orthogonal cutting. In another study carried out
by G. Chen et al.15, a Johnson-Cook material model with
an energy-based ductile-failure criterion was developed
using a titanium-alloy (Ti–6Al–4V) high-speed machin-
ing FEA. D. Umbrello16 presented a finite-element anal-
ysis (FEA) of machining TiAl6V4 for both conventional
and high-speed cutting regimes. Work to date has shown
that little work has been carried on the determination of
Materiali in tehnologije / Materials and technology 51 (2017) 6, 953–956 953
MATERIALI IN TEHNOLOGIJE/MATERIALS AND TECHNOLOGY (1967–2017) – 50 LET/50 YEARS
UDK 52-17:62-493-026.775:621.9 ISSN 1580-2949
Original scientific article/Izvirni znanstveni ~lanek MTAEC9, 51(6)953(2017)
the chip formation when machining AISI304 stainless
steels. In a study carried out by J. Q. Xie et al.17, the
theory of shear banding was included in the analysis of
chip formation and chip instability. They used analytic
and experimental methods to study these characteristics.
This work aims to investigate the serrated-chip formation
in the machining of the AISI304 stainless steel using
finite-element simulations.
2 EXPERIMENTAL PART
2.1 Turning process
Turning processes were performed on a CNC turning
lathe that has a capacity of 10kW using AISI 1045
samples with dimensions of Ø50 mm × 100 mm. The
rake angle was 0° and the clearance angle was 5°. The
turning processes were carried out using the turning
parameters from Table 1. The cutting length for the
turning processes was chosen to be 10 mm.
Table 1: Turning parameters
Parameters Value
Cutting speed – Vc (m/min) 100
Feed rate – f (min–1) 0.1
Depth of cut – ap (mm) 0.5
2.2 Numeric analysis
In 2D numeric simulations, the cutting tool and the
workpiece consist of a tetrahedral mesh. While the mesh
structure of the workpiece consists of 1453 elements and
1547 nodes, the mesh structure of the cutting tool
consists of 770 elements and 823 nodes. The mesh
structure of the model of the workpiece and cutting tool
is given in Figure 1. However, the workpiece model was
constrained by the lateral surfaces and lower surface.
The contact algorithm for the interface of the cutting tool
and workpiece was defined as the master and slave in the
software. As the friction model for these two elements,
the Coulomb model of friction was selected because it
uses low cutting speeds. The Cockcroft-Latham fracture
criterion was selected as the damage criterion. The
Cockcroft-Latham criterion is given in Equation (1).
According to the Cockcroft-Latham damage criterion,
damage occurs when the accumulated stress state D, over
the plastic strain, reaches the critical damage value
(Dcr). The Dcr was selected to be 90 for all the cutting
simulations because it had the most suitable chip form.
The friction coefficient for the simulation study was
calculated to be 0.41 for the normal machining and 0.60
for the damage criterion. This coefficient of the friction
between the tool and the chip in orthogonal cutting was
calculated using Equations (2) and (3).18 Fc and Ft forces
were obtained experimentally; Fs, Ns, F and N forces
depend on them and can be calculated from Figure 2.
D d
f
= ∫  

1
0
(1)
A. GÖK: 2D NUMERIC SIMULATION OF SERRATED-CHIP FORMATION IN ORTHOGONAL CUTTING OF AISI316H ...
954 Materiali in tehnologije / Materials and technology 51 (2017) 6, 953–956
MATERIALI IN TEHNOLOGIJE/MATERIALS AND TECHNOLOGY (1967–2017) – 50 LET/50 YEARS
Figure 2: Two-dimensional (2D) force system in turning operations (Merchant’s force circle)
Figure 1: Mesh process
μ = tan 
 =
F
N
(2)
μ =
F F
F F
t c
c t
+
−
tan
tan


(3)
2.3 Material model
While the workpiece was selected as AISI 316h, the
cutting tool was selected to be tungsten carbide (WC).
The mechanical and thermal properties of the WC and
AISI 316h are given in Table 2.19 The flow-stress curve
of the workpiece-material model was taken from refe-
rence19. The flow stress was defined as a function of the
strain, strain rate and temperature as seen in Figure 3.
The flow stress () in Equation (4) was selected to ex-
hibit the true material behavior as a function of the effec-
tive plastic strain (), effective strain rate () and tempe-
rature (T). The flow-stress curves are very important for
high-temperature applications such as metal cutting.
  = ( ,  , )T (4)
Table 2: Mechanical and thermal properties of the drill bit and bone
materials19
Workpiece-material properties (AISI 316h316H)
Modulus of elasticity (GPa) 20 °C (210)
Poisson’s ratio 0.3
Thermal-expansion coefficient
(10–6 °C–1) 93.33 °C (1.20×10
–5)
Thermal conductivity(W/mK) 100 °C (17)
Heat capacity (N/mm2 °C) 93.33 °C (2.78)
Emissivity 0.7
Cutting-tool-material properties (WC)
Modulus of elasticity (GPa) 650
Poisson’s ratio 0.25
Thermal-expansion coefficient
(10–6 °C–1) 5
Thermal conductivity(W/mK) 59
Heat capacity (N/s /mm/°C) 15
Emissivity 0
3 RESULTS
At the end of the study, force variations occurred in
the normal machining (NM) and the machining with
damage criterion (MWDC) was very different, as seen in
Figure 4. As seen in Table 3, while the MWDC de-
formed-chip thickness was lower than during the NM,
the chip ratio and shear-angle values were higher during
the MWDC than during the NM. Good agreement bet-
ween experimental tests and FEM simulations was found
for cutting forces and shear-angle values, as shown in
Figures 5 and 6.
A. GÖK: 2D NUMERIC SIMULATION OF SERRATED-CHIP FORMATION IN ORTHOGONAL CUTTING OF AISI316H ...
Materiali in tehnologije / Materials and technology 51 (2017) 6, 953–956 955
MATERIALI IN TEHNOLOGIJE/MATERIALS AND TECHNOLOGY (1967–2017) – 50 LET/50 YEARS
Figure 5: Deformed-chip thickness and shear angles for the NM and
MWDCFigure 3: Flow-stress curves for the workpiece material19
Figure 4: Force variations occurred during NM and MWDC
the chip formation when machining AISI304 stainless
steels. In a study carried out by J. Q. Xie et al.17, the
theory of shear banding was included in the analysis of
chip formation and chip instability. They used analytic
and experimental methods to study these characteristics.
This work aims to investigate the serrated-chip formation
in the machining of the AISI304 stainless steel using
finite-element simulations.
2 EXPERIMENTAL PART
2.1 Turning process
Turning processes were performed on a CNC turning
lathe that has a capacity of 10kW using AISI 1045
samples with dimensions of Ø50 mm × 100 mm. The
rake angle was 0° and the clearance angle was 5°. The
turning processes were carried out using the turning
parameters from Table 1. The cutting length for the
turning processes was chosen to be 10 mm.
Table 1: Turning parameters
Parameters Value
Cutting speed – Vc (m/min) 100
Feed rate – f (min–1) 0.1
Depth of cut – ap (mm) 0.5
2.2 Numeric analysis
In 2D numeric simulations, the cutting tool and the
workpiece consist of a tetrahedral mesh. While the mesh
structure of the workpiece consists of 1453 elements and
1547 nodes, the mesh structure of the cutting tool
consists of 770 elements and 823 nodes. The mesh
structure of the model of the workpiece and cutting tool
is given in Figure 1. However, the workpiece model was
constrained by the lateral surfaces and lower surface.
The contact algorithm for the interface of the cutting tool
and workpiece was defined as the master and slave in the
software. As the friction model for these two elements,
the Coulomb model of friction was selected because it
uses low cutting speeds. The Cockcroft-Latham fracture
criterion was selected as the damage criterion. The
Cockcroft-Latham criterion is given in Equation (1).
According to the Cockcroft-Latham damage criterion,
damage occurs when the accumulated stress state D, over
the plastic strain, reaches the critical damage value
(Dcr). The Dcr was selected to be 90 for all the cutting
simulations because it had the most suitable chip form.
The friction coefficient for the simulation study was
calculated to be 0.41 for the normal machining and 0.60
for the damage criterion. This coefficient of the friction
between the tool and the chip in orthogonal cutting was
calculated using Equations (2) and (3).18 Fc and Ft forces
were obtained experimentally; Fs, Ns, F and N forces
depend on them and can be calculated from Figure 2.
D d
f
= ∫  

1
0
(1)
A. GÖK: 2D NUMERIC SIMULATION OF SERRATED-CHIP FORMATION IN ORTHOGONAL CUTTING OF AISI316H ...
954 Materiali in tehnologije / Materials and technology 51 (2017) 6, 953–956
MATERIALI IN TEHNOLOGIJE/MATERIALS AND TECHNOLOGY (1967–2017) – 50 LET/50 YEARS
Figure 2: Two-dimensional (2D) force system in turning operations (Merchant’s force circle)
Figure 1: Mesh process
μ = tan 
 =
F
N
(2)
μ =
F F
F F
t c
c t
+
−
tan
tan


(3)
2.3 Material model
While the workpiece was selected as AISI 316h, the
cutting tool was selected to be tungsten carbide (WC).
The mechanical and thermal properties of the WC and
AISI 316h are given in Table 2.19 The flow-stress curve
of the workpiece-material model was taken from refe-
rence19. The flow stress was defined as a function of the
strain, strain rate and temperature as seen in Figure 3.
The flow stress () in Equation (4) was selected to ex-
hibit the true material behavior as a function of the effec-
tive plastic strain (), effective strain rate () and tempe-
rature (T). The flow-stress curves are very important for
high-temperature applications such as metal cutting.
  = ( ,  , )T (4)
Table 2: Mechanical and thermal properties of the drill bit and bone
materials19
Workpiece-material properties (AISI 316h316H)
Modulus of elasticity (GPa) 20 °C (210)
Poisson’s ratio 0.3
Thermal-expansion coefficient
(10–6 °C–1) 93.33 °C (1.20×10
–5)
Thermal conductivity(W/mK) 100 °C (17)
Heat capacity (N/mm2 °C) 93.33 °C (2.78)
Emissivity 0.7
Cutting-tool-material properties (WC)
Modulus of elasticity (GPa) 650
Poisson’s ratio 0.25
Thermal-expansion coefficient
(10–6 °C–1) 5
Thermal conductivity(W/mK) 59
Heat capacity (N/s /mm/°C) 15
Emissivity 0
3 RESULTS
At the end of the study, force variations occurred in
the normal machining (NM) and the machining with
damage criterion (MWDC) was very different, as seen in
Figure 4. As seen in Table 3, while the MWDC de-
formed-chip thickness was lower than during the NM,
the chip ratio and shear-angle values were higher during
the MWDC than during the NM. Good agreement bet-
ween experimental tests and FEM simulations was found
for cutting forces and shear-angle values, as shown in
Figures 5 and 6.
A. GÖK: 2D NUMERIC SIMULATION OF SERRATED-CHIP FORMATION IN ORTHOGONAL CUTTING OF AISI316H ...
Materiali in tehnologije / Materials and technology 51 (2017) 6, 953–956 955
MATERIALI IN TEHNOLOGIJE/MATERIALS AND TECHNOLOGY (1967–2017) – 50 LET/50 YEARS
Figure 5: Deformed-chip thickness and shear angles for the NM and
MWDCFigure 3: Flow-stress curves for the workpiece material19
Figure 4: Force variations occurred during NM and MWDC
4 CONCLUSIONS
In this study, a finite-element model was developed
to see the effect of a serrated-chip formation in the ma-
chining of the AISI304 stainless steel using finite-ele-
ment simulations. A computer-aided numerical simula-
tion of the turning process was also performed using
DEFORM – 2D software. It can be said that the 2D FEM
model gives reasonable results compared to the experi-
mental results in view of cutting forces, thrust force and
shear angles. This proves the accuracy of the developed
2D FEM model, which can be used for this type of
turning simulations.
5 REFERENCES
1 S. Coromant, Modern metal cutting: a practical handbook, Sandvik
Coromant Press, 1st ed., 1994
2 M. P. Groover, Fundamentals of Modern Manufacturing: Materials,
Processes, and Systems, Prentice Hall, Wiley, 1996
3 E. M. Trent, Metal Cutting, Elsevier Science, Butterworth-Heine-
mann, 2016
4 J. Paro, H. Hänninen, V. Kauppinen, Tool wear and machinability of
X5 CrMnN 18 18 stainless steels, Journal of Materials Processing
Technology, 119 (2001), 14–20, doi:10.1016/S0924-0136(01)
00877-9
5 D. O’Sullivan, M. Cotterell, Machinability of austenitic stainless
steel SS303, Journal of Materials Processing Technology, 124
(2002), 153–159, doi: 10.1016/S0924-0136(02)00197-8
6 L. Jiang, Å. Roos, P. Liu, The influence of austenite grain size and its
distribution on chip deformation and tool life during machining of
AISI 304L, Metallurgical and Materials Transactions A, 28 (1997),
2415–2422, doi: 10.1007/s11661-997-0198-z
7 T. H. C. Childs, Material Property Needs in Modeling Metal
Machining, Machining Science and Technology, 2 (1998), 303–316,
doi:10.1080/10940349808945673
8 M. C. Shaw, Metal Cutting Principles, Oxford University Press, 2005
9 K. Maekawa, T. Obikawa, Y. Yamane, T. H. C. Childs, Metal Ma-
chining: Theory and Applications, Elsevier Science, 2013
10 V. P. Astakhov, Metal Cutting Mechanics, Taylor & Francis, 1998
11 M. Bäker, The influence of plastic properties on chip formation,
Computational Materials Science, 28 (2003), 556–562, doi:10.1016/
j.commatsci.2003.08.013
12 T. Ozel, M. Sima, A. Srivastava, Finite element simulation of high
speed machining Ti-6Al-4V alloy using modified material models,
Transactions of the NAMRI/SME, 38 (2010), 49–56,
13 M. Sima, T. Özel, Modified material constitutive models for serrated
chip formation simulations and experimental validation in machining
of titanium alloy Ti–6Al–4V, International Journal of Machine Tools
and Manufacture, 50 (2010), 943–960, doi:10.1016/j.ijmachtools.
2010.08.004
14 R. Alvarez, R. Domingo, M. A. Sebastian, The formation of saw
toothed chip in a titanium alloy: influence of constitutive models,
Journal of Mechanical Engineering, 57 (2011), 739–749,
doi:10.5545/sv-jme.2011.106
15 G. Chen, C. Ren, X. Yang, X. Jin, T. Guo, Finite element simulation
of high-speed machining of titanium alloy (Ti–6Al–4V) based on
ductile failure model, The International Journal of Advanced Manu-
facturing Technology, 56 (2011), 1027–1038, doi:10.1007/s00170-
011-3233-6
16 D. Umbrello, Finite element simulation of conventional and high
speed machining of Ti6Al4V alloy, Journal of Materials Processing
Technology, 196 (2008), 79–87, doi:10.1016/j.jmatprotec.2007.
05.007
17 J. Q. Xie, A. E. Bayoumi, H. M. Zbib, Analytical and experimental
study of shear localization in chip formation in orthogonal machin-
ing, Journal of Materials Engineering and Performance, 4 (1995),
32–39, doi: 10.1007/bf02682702
18 P. J. Arrazola, T. Özel, Investigations on the effects of friction mo-
deling in finite element simulation of machining, International
Journal of Mechanical Sciences, 52 (2010), 31–42, doi:10.1016/
j.ijmecsci.2009.10.001
19 DEFORM-3D Material Library, http://home.zcu.cz/~sbenesov/
Deform2Dlabs.pdf, 12.04.2017
A. GÖK: 2D NUMERIC SIMULATION OF SERRATED-CHIP FORMATION IN ORTHOGONAL CUTTING OF AISI316H ...
956 Materiali in tehnologije / Materials and technology 51 (2017) 6, 953–956
MATERIALI IN TEHNOLOGIJE/MATERIALS AND TECHNOLOGY (1967–2017) – 50 LET/50 YEARS
Figure 6: a) Cutting and b) thrust force for MWDC
Table 3: Comparison of NM and MWDC
Cutting speed
(m/min)
Undeformed chip
thickness, t (mm)
Deformed chip
thickness, tc (mm)
Chip ratio, rc Shear angle, (with Eg. 17)
Shear angle, 
(FEM)
NM 100 0.5 1.85 0.268 15 17
MWDC 100 0.5 0.76 0.657 33.304 37
A. GÖK et al.: EFFECTS OF CUTTING PARAMETERS AND TOOL-PATH STRATEGIES ON TOOL ACCELERATION ...
957–965
EFFECTS OF CUTTING PARAMETERS AND TOOL-PATH
STRATEGIES ON TOOL ACCELERATION IN BALL-END
MILLING
U^INKI REZALNIH PARAMETROV IN STRATEGIJA ZA POSPE[EK ORODJA
PRI MEHANSKI OBDELAVI S KROGLI^NIM FREZALOM
Arif Gök1, Kadir Gök2, Mehmet Burak Bilgin1, Mehmet Ali Alkan3
1Amasya University, Faculty of Technology, Department of Mechnical Engineering, 05100 Amasya, Turkey
2Celal Bayar University, Favulty of Technology, Department of Mechanical and Manufacturing Engineering, 45100 Manisa, Turkey
3Mu

gla Sitki Kocman University, Ula Vocational High School, Department of Energy, 48000 Mu

gla, Turkey
arif.gok@amasya.edu.tr
Prejem rokopisa – received: 2017-04-08; sprejem za objavo – accepted for publication: 2017-06-22
doi:10.17222/mit.2017.039
The determination of the cutting-parameter values that cause increases in vibration values is important to minimize the errors
that can occur. Thus, the first aim of this study was to investigate the optimum cutting-parameter values and tool-path strategies
in ball-end milling of the EN X40CrMoV5-1 tool steel with three coated cutters using the Taguchi method. The parameters
taken into consideration are the cutting speed, feed rate, step over and tool-path strategies. The second aim of the study, a model
for the tool acceleration as a function of the cutting parameters, was obtained using the response-surface methodology (RSM).
As a result, the most effective parameter within the selected cutting parameters and cutting strategies for both inclined surfaces
and different coatings was the step over. In terms of tool coatings, the most deteriorating coating for the tool acceleration on
both inclined surfaces was the TiC coating. In addition, the response-surface methodology is employed to predict the
tool-vibration values depending on the cutting parameters and tool-path strategy. The model generated gives highly accurate
results.
Keywords: inclined surfaces, ball-end milling, tool acceleration, Taguchi method, response-surface methodology, response
optimization
Neoptimalni rezalni parametri med mehansko obdelavo lahko povzro~ijo ne`elene vibracije in posledi~no napake. Prvi cilj
avtorjev te {tudije je bil dolo~iti optimalne vrednosti rezalnih parametrov in strategije potovanja orodja med mehansko obdelavo
orodnega jekla EN X40CrMoV5-1 s krogli~nim frezalom s tremi rezili z razli~no prevleko (TiC, TiN in TiAlN). Za to so upora-
bili Taguchi-jevo metodo. Parametri, ki so jih avtorji zajeli v {tudiji so bili: hitrost rezanja, velikost odvzema, korak odvzema
(preskok) in strategija poti orodja. Drugi cilj avtorjev te {tudije je bil izdelati model pospe{evanja orodja v odvisnosti od
rezalnih parametrov, z uporabo metodologije odziva povr{ine (angl. RSM). Ugotovili so, da je korak odvzema (angl.: step over)
naju~inkovitej{i parameter med izbranimi rezalnimi parametri in rezalnimi strategijami, tako za oba izbrana nagiba
(ukrivljenosti) povr{ine, kot tudi izbrane trde prevleke. Med izbranimi trdimi prevlekami se je v vseh pogojih frezanja kot
najslab{a izkazala TiC prevleka. RSM metodologija dodatno omogo~a napoved vibracij orodja v odvisnosti od rezalnih
parametrov in izbrane strategije poti orodja. Izdelani model daje zelo to~ne rezultate.
Klju~ne besede: nagib (ukrivljenost) povr{ine, mehanska obdelava s krogli~nim frezalom, pospe{ek orodja, Taguchi metoda,
metodologija odgovora povr{ine, optimizacija odgovora
1 INTRODUCTION
Nowadays, machining is one of the most important
methods for manufacturing technologies and it remains
up-to-date.1 In the machining of inclined surfaces, tight
machining tolerances are generally requested for the
processes of finishing and semi-finishing, which are
accomplished using indexable insert ball-end mills.2,3
The forces that occur at high cutting speeds, especially
during hard machining, and at high rates of metal
removing, cause excessive, irregular vibrations of cutting
tools during the machining. These vibrations cause the
cutting tools to break, disrupting the process stability and
the quality. Therefore, generating the optimum cutting
parameters is crucial to obtain high productivity in the
manufacturing process of complex geometries and to
reach the desired tolerance values.4,5 The studies carried
out in the field commonly focus on:
1) the effect of cutting parameters and cutting strategies
of plain-surface milling,
2) analytical tool-acceleration calculations and measure-
ments for end-milling and turning operations.
W. H. Yang and Y. S. Tarng6 worked on the optimi-
zation of the cutting parameters for turning operations so
that both optimum cutting parameters were demonstrated
and the basic cutting parameters affecting the cutting
performance in turning were defined.
M. Kurt et al.7 worked on the optimization of the
cutting parameters for the finish surface and the accuracy
of the hole diameter during dry drilling. In this way,
optimum cutting conditions were obtained with the
process optimization.
C. Gologlu and N. Sakarya8 investigated the effects
of tool-path strategies on the surface roughness for
pocket-milling operations using cutting parameters with
Materiali in tehnologije / Materials and technology 51 (2017) 6, 957–965 957
MATERIALI IN TEHNOLOGIJE/MATERIALS AND TECHNOLOGY (1967–2017) – 50 LET/50 YEARS
UDK 621.927:621.9.07:621.926.5 ISSN 1580-2949
Original scientific article/Izvirni znanstveni ~lanek MTAEC9, 51(6)957(2017)