Experimental Approach of CNC Drilling Operation for Mild Steel Using Taguchi...
Tool Wear.Rep
1. 1
Tool Wear and the Relationship
with Cutting Conditions
Dominick Colwill
1132090
2. 2
Declaration
I hereby declare:
that except where reference has clearly been made to work by others, all the work
presented in this report is my own work;
that it has not previously been submitted for assessment; and
that I have not knowingly allowed any of it to be copied by another student.
I understand that deceiving or attempting to deceive examiners by passing off the work of
another as my own is plagiarism. I also understand that plagiarising the work of another or
knowingly allowing another student to plagiarise from my work is against the University
regulations and that doing so will result in loss of marks and possible disciplinary
proceedings against me.
Signed …………………………………………
Date …………………………………………
3. 3
Acknowledgments
I would like to acknowledge the help of Renishaw for the opportunity to visit a large
manufacturing facility and also the valuable insights into modern manufacturing’s approach
to tool management. I would also like to thank Cardiff University’s technicians, in particular
Craig, for carrying out the machining processes in the lab and creating the test pieces. Lastly
I’d like to thank my supervisor Paul Prickett who gathered and distributed the results from
testing as well as providing insightful knowledge and direction throughout the project.
Abstract
Tool management is an important part of manufacturing. In industry tool monitoring is seen
as non-productive, therefore tools are discarded before there’s any risk of them failing,
leading to wasted tool life and a decreased efficiency in the manufacturing process.
This report covers the process of designing and carrying out a test to better understand the
effects of wear on tool and part geometry during a CNC process in order to provide a
platform for future studies into the tool management field.
The design of the test is examined as well as expected outcomes and the testing process.
Results of the component geometries of diameter and circularity showed a strong
correlation between wear and a decrease in how circular the component became. Also
found was evidence of the tool flank profile becoming more stepped as wear progressed.
Furthermore the tests own Taylor constants of n and C were discovered to be different from
typically expected values.
4. 4
Contents
Introduction ...............................................................................................................................6
1 Definitions...............................................................................................................................7
1.1 Nomenclature................................................................................................................... 7
1.2 Cutting Equations ............................................................................................................. 8
1.3 Circularity ......................................................................................................................... 9
2 Tool Wear..............................................................................................................................10
2.1 Description and classification......................................................................................... 10
2.2 Progression of wear ....................................................................................................... 11
3 Tool life..................................................................................................................................13
3.1 Description and classification......................................................................................... 13
3.2 Effects of cutting conditions on tool life........................................................................ 13
3.3 Taylor equation .............................................................................................................. 14
3.4 Tool wear and tool life in industry ................................................................................. 17
4 Test Design............................................................................................................................19
4.1 Milling Equipment .......................................................................................................... 19
4.2 Metrology methods........................................................................................................ 20
4.3 Coordinate measuring machine (CMM)......................................................................... 22
6. 6
Introduction
Thanks to advancement in quality management methods introduced by the likes of Deming
and Taguchi, and the technological advances in the field of metrology and machining, the
quality of goods and the efficiency they are being produced at by the manufacturing
industry are better than they ever have been. The application of computers in machining
has become much more widespread, meaning nowadays a trained employee can rely on a
CNC machine to produce complex and highly accurate components with minimal
supervision, leaving them free to supervise other machinery. However, quality and
efficiency need to always be improved.
All things eventually wear out, however the most frequently changed components of a CNC
machine are the cutting tools. Tooling costs for large manufacturers are astronomical, often
in the hundreds of thousands of pounds, however in the area of tool management the
requirements of industry have begun to outstrip the scientific community. The lack of a
measurable answer to the effects of tool wear during a CNC machining process leave
manufacturers relying on past knowledge and experience. This approach and the
unproductivity associated with metrology mean that tools are often changed long before
they’re expected to fail to avoid the potential costs associated with tool failure.
This investigation aims to produce a method of further understanding the effects of wear on
cutting tools with the development of a repeatable test. Then using knowledge gained to
suggest future directions of study that would aid the measuring and by extension the
prolonging of tool life while maintaining the emphasis behind the quote “Quality is free”
(Crosby 1979).
7. 7
1 Definitions
1.1 Nomenclature
𝑥 Width of cut (mm)
𝑦 Depth of cut (mm)
𝑓𝑧 Feed per tooth (mm)
𝑓𝑛 Feed per cut (mm/rev)
𝑁 Spindle speed (rpm)
𝑉𝑐 Cutting speed (m/min)
𝑉𝑓 Table feed (mm/min)
𝑍 Number of effective teeth
𝑄 Metal removal rate (cm3/min)
𝑇 Tool life (min)
𝑛 Taylor constant relating to tool
material
𝐶 Cutting speed for tool life of 1
minute
(m/min)
𝑎 Constant relating to feed per cut
𝑏 Constant relating to depth of cut
MVCS Matrix Vertical Center Smart 430A
CNC Computer Numerical Control
CAD Computer Aided Design
CMM Coordinate Measurement Machine
HSS High Speed Steel
8. 8
1.2 Cutting Equations
Due to the multitude of parameters involved in multi-point metal cutting operations there
are a number of different definitions that are used in order to calculate and define them.
Cutting speed (Vc) – The difference in speed between the rotation of the cutting edge and
the surface of the component it is working on. Often ideal cutting speeds for particular tool
and workpiece materials are suggested by machinists’ handbooks and tool manufacturers.
From this value and also the diameter of the cut (x) the spindle speed (N) can then be
calculated using equation ( 1 ):
𝑉𝑐 =
𝜋 × 𝑥 × 𝑁
1000
( 1 )
Feed per cut (fn) – Often referred to as feed rate is the speed at which the tool advances
through the workpiece. Similarly to cutting speed optimal values are usually suggested by
machinists’ handbooks and tool manufacturers depending on the materials of the tool and
the workpiece. From this table feed (Vf) and consequently feed per tooth (fz) can be
calculated with the use of the following equations ( 2 ) and ( 3 ):
𝑓𝑛 =
𝑉𝑓
𝑁
( 2 )
9. 9
𝑓𝑧 =
𝑉𝑓
𝑁 × 𝑍
( 3 )
Metal removal rate (Q) – The amount of material being removed by the cutter each minute
is known as the metal removal rate. It is useful as it enables the prediction of total milling
time which in turn enables approximations at a processes effects on a cutting tools life.
𝑄 =
𝑦 × 𝑥 × 𝑉𝑓
1000
( 4 )
1.3 Circularity
Circularity (Figure 1), otherwise known as the roundness, describes the difference in radius
from a common centre point of the largest and smallest radii of a circular object. So, an
object with a circularity value of 0 is a perfect circle.
Measured ‘circular’ object
Circle with radius r2
Circle with radius r1
Circularity
Figure 1 - Definition of circularity.
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2 Tool Wear
2.1 Description and classification
High forces and temperatures during a metal cutting process form a very harsh environment
for a tool that can often result in tool failure. There are three modes in which a cutting tool
can fail during machining (Groover 2013):
1. Fracture failure occurs when the cutting force at the tool point is too great, this
creates a very sudden brittle fracture. Fracture failure is undesirable as it renders the
cutting tool completely useless, resulting in the premature loss of the tool.
2. Temperature failure is seen when the cutting temperature is too high for the
material of the tool. This causes the tool point to soften and allows the tool to be
plastically deformed. This sort of failure is also undesirable as using a deformed tool
could produce unwanted variations in the work surface.
3. Progressive wear of the cutting edge causes a reduction in cutting efficiency and a
change in tool shape. This gradual wear can eventually lead to fracture or
temperature failures if the tool becomes heavily worn. This form of wear is preferred
as it leads to the longest time of use with the tool which brings with it the economic
advantages of spending less money and time swapping out damaged tools.
Other advantages of progressive tool failure are the variations caused by a gradual failure
can be measured and accounted for by updating machine offsets during the production
process. This is opposed to a fracture or temperature failure happening suddenly during a
process which often causes damage to a component. In order for product quality to remain
high, the damage caused would need to be reworked or completely scrapped altogether,
11. 11
reducing the process capability of a system. Premature tool failure can be avoided by
selecting cutting conditions that are favourable to the specific tool and workpiece and by
changing the tool before its cutting edge is too heavily worn.
Progressive wear occurs principally in two locations.
Gradual failure of the tool rake face is known as crater
wear while gradual failure of the relief face is known
as flank wear. (Figure 2)
Crater wear occurs in the form of a cavity in the rake
face of the tool that is created during the sliding of the chip material against the surface.
High forces and temperatures cause chip material to fuse to the tool surface, when this
material is forced out by following chip it takes some of the tool surface with it. Often either
too high cutting speeds or feeds per cut will result in the high temperatures and forces
needed to produce crater wear.
Abrasive action caused by rubbing between the newly created work face and the relief face
of the tool results in flank wear. Flank wear creates a poor surface finish to components as
well as the potential for them to be out of tolerance, causing rework and potential
scrappage. Excessive flank wear is often the fault of a too high cutting speed.
2.2 Progression of wear
Throughout a tools life the amount and rate of wear it experiences varies due to changes in
the wear mechanisms. The typical relationship between tool cutting time and wear is shown
in Figure 3. Three distinct regions along the curve can be seen, the first region occurs during
Rake face Relief face
Cuttingedge
Figure 2 - End mill cutter features.
12. 12
the first few minutes of cutting and is known as the break in period. During this period initial
wear is established, rapidly degrading the sharp cutting edge of the tool. This period of rapid
initial wear is followed by the steady wear stage, a period during which the wear increases
at a uniform rate. In Figure 3 this
period is characterised as a linear
function, however in actual
machining there would be expected
to be deviations from this line. A
long steady wear stage is desired
during machining processes as it is
possible to predict and therefore compensate for the changes in tool geometry. In
computerised numerical controlled (CNC) processes this would involve updating the tool
offsets, a procedure that lets the controller know the dimensions of the tool relative to a
standard gauge line, therefore enabling it to compensate for any changes in dimensions
when machining the next component. After the period of steady wear, the wear reaches a
point where its rate of increase begins to accelerate, this denotes the failure of the tool. At
this severe wear stage the cutting edge has degraded so much that temperature and cutting
forces are observed to also increase (Kolar et al. 2015) at an increasing rate, reducing the
efficiency of the process. If the tool is not replaced and is allowed to carry on machining it
will eventually succumb to a temperature failure which as mentioned earlier could result in
damaged to the machined component or the machine.
Wear(mm)
Cutting Time (min)
Figure 3 - Wear in relation to cutting time.
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3 Tool life
3.1 Description and classification
Tool life is “the time a tool can be reliably used for cutting before it must be discarded or
repaired” (Yan et al. 2009, p. 142). The life of a particular tool can be defined by operating
the tool until it fails, however due to the reasons mentioned earlier it is not desirable to
cause a sudden tool failure. Therefore in practice, tool life is the amount of time, measured
in minutes, between two consecutive tool changes, after which time the tool will need to be
either reground to restore its cutting edge or discarded. Tool life is known to be affected by
multiple factors relating to the tool such as geometry and material as well as factors relating
to cutting conditions such as cutting speeds, component material hardness and the
lubrication used, making determining and predicting the life of a tool extremely complicated
despite the extensive research in the area.
3.2 Effects of cutting conditions on tool life
When carrying out a metal cutting operation, it is important to know the effects of varying
cutting conditions. Figure 4 shows the widely accepted effects of varying the three
controllable cutting conditions on tool life. By far the greatest reduction in tool life is as a
Toollife(min)
Toollife(min)
Cutting speed Vc (m/min) Feed per cut fn (mm/rev) Cutting depth ap (mm)
Toollife(min)
Figure 4 - Effects of varying cutting conditions on tool life.
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result of increasing the cutting speed. Increasing the cutting speed increases the abrasion
effect of the tool relief face which in turn increases friction leading to high temperatures
and often plastic deformation of the tool. The next most influential cutting condition is the
feed per cut followed by the cutting depth. Typically, as a rule of thumb the cutting depth
should be no deeper than the radius of the tool being used.
3.3 Taylor equation
F. W. Taylor (1907) produced an equation to describe tool life throughout the steady wear
stage of a tool, in an attempt to identify ways of more economically utilising cutting tools:
𝑉𝑐 𝑇 𝑛
= 𝐶 ( 5 )
The equation has been widely used in industry in the past to help optimise tool usage and
component quality. The parameters n and C are known as Taylor constants. The value for n
is a constant relating to the material of the tool and the value for C is dependent on tool
material, work material and cutting conditions. Applying natural logarithms to ( 5 ) yields
equation ( 6 ):
𝑙𝑛𝑉𝑐 + 𝑛𝑙𝑛𝑇 = 𝑙𝑛𝐶
𝑙𝑛𝑉𝑐 = 𝑙𝑛𝐶 − 𝑛𝑙𝑛𝑇 ( 6 )
15. 15
Producing equation ( 6 ) in this way and plotting it to a log graph as in Figure 5 shows the
value of the intercept C to be equal to that of the cutting speed (Vc) when the tool life (T) is
equal to one minute. Also
attainable from Figure 5 is
the value of n, which is
determined by finding the
slope of the graph.
Although throughout much of
the 20th century the Taylor
equation was an extremely useful theory, in modern manufacturing, particularly with the
more widespread use of CNC operations and the variability in machining that has brought,
limitations arise with the use of the equation. For example equation ( 5 ) only takes into
consideration the cutting parameter of Vc and it ignores the smaller but also significant
effects of changing the parameters of cutting depth (ap) and feed per cut (fn) on wear rates.
Thus an extended Taylor model was formulated to account for these effects (Yan et al.
2009):
𝑉𝑐 𝑇 𝑛
𝑓𝑛
𝑎
𝑦 𝑏
= 𝐶 ( 7 )
𝑇 = 𝐶
1
𝑛 𝑉𝑐
−
1
𝑛
𝑓𝑛
−
𝑎
𝑛
𝑦
−
𝑏
𝑛
( 8 )
Where a and b in equations ( 7 ) and ( 8 ) are introduced constants relating to feed per cut
and depth of cut that can only be determined experimentally. Typically the values of a and b
1
T (min)
100
Vc(m/min)
10
Figure 5 - Natural log-log plot of cutting speed against tool
life.
16. 16
are less than one, with a being greater than b to reflect the lesser effect that depth of cut
has compared with feed per cut and the lesser effect feed per cut has compared with
cutting speed on tool life. Although the extended equation ( 8 ) is more in depth than the
original Taylor equation ( 5 ), issues with its accuracy arise when considering cutting
operations using multi point tools and more complex cutting geometries. So although a
cutters diameter may be 16 mm, it will not always be cutting 16 mm strips, for example
during finishing operations the width of the cut will be marginal compared with the original
process of boring out the component. Another consideration is the amount of teeth on the
cutter as this affects chip size and cutting forces, with knowledge of the mechanisms of tool
wear it is therefore possible to assume that different amounts of wear will occur when
these parameters are altered. For this reason it is necessary to further improve the equation
to account for these changes. Equation ( 10 ) shows equation ( 8 ) expanded with the
cutting equations from earlier to provide a method of accounting for the possible changes in
the cut width and number of teeth the tool has:
𝑇 = 𝐶
1
𝑛 (
𝜋𝑥𝑁
1000
)
−
1
𝑛(𝑓𝑧 𝑍)
−
𝑎
𝑛 𝑦
−
𝑏
𝑛
( 9 )
𝑇 = (1000𝐶𝑦−𝑏
(𝜋𝑥𝑁)−1
(𝑓𝑧 𝑍)−𝑎
)
1
𝑛 ( 10 )
17. 17
3.4 Tool wear and tool life in industry
Despite the economic advantages of utilising the whole life of a tool and the amount of
research that has been carried out in the area of tool wear and extending tool life,
businesses in the manufacturing industry still tend to carry out a “better safe than sorry”
attitude when changing and replacing tools, often swapping them when they’re at only 60%
of their life leading to huge wastage. On top of this the Taylor equation and its extensions
are very rarely used, preferring to rely on their own experience in order to gauge what the
predicted life of a tool may be. There are multiple reasons for this.
The first reason is that there are too many independent variables involved with the
calculation of tool life, this means that the tool life would need to be calculated for every
single different cut in order to gain an accurate and reliable life of the tool. This would add
increased time and effort to the machining process with potentially not a great reward in
life.
Secondly, the cost of disposing of a tool that isn’t yet worn out is likely less than the cost of
scrapping or having to rework a component that has been damaged by the sudden failure of
a tool. If the tool is less expensive than the component it is machining then it is not
economical to risk the quality of the component for the sake of gaining extra tool life.
Thirdly are the multiple effects outside of the actual cutting process that also can have an
impact on the length of tool life. The application of differing cutting fluids is known to
change the amount of wear a tool experiences, also taken into account is the effect that
wear has upon other machining dynamics such as vibration which if allowed to increase
18. 18
unchecked can cause chatter and damage to not only the workpiece but also parts of the
milling machines.
Investigations have been made into the effects of increased wear on the vibrations
produced during machining (Wojciechowski et al. 2014), the investigation was carried out
during a ball end milling process of hardened steel using cubic boron nitride and tungsten
carbide cutting tools. Flank wear was measured using a microscope at regular intervals
throughout the testing and induced vibrations were recorded using a piezoelectric force
dynamometer. The findings are displayed in Figure 6. It is possible to see by the positive
correlation between the flank wear (VBB) and the acceleration of the vibrations (Ai) that
measured vibrations do indeed increase with a deteriorating tool flank wear. Issues such as
this further complicate the issue of tool life extension for manufacturers as the increase in
induced vibrations could have negative impacts on component quality even though the tool
is still within its useable life. Another factor is that the counter measure to vibrations is
often to slow the process down, however this reduces a machines productivity which could
offset the cost of the time saved in not replacing the tool.
Figure 6 - Measured RMS values of acceleration of vibrations in function of tool wear for the
tungsten carbide (WC) and cubic boron nitride (CBN) tools. (Wojciechowski et al. 2014)
19. 19
4 Test Design
4.1 Milling Equipment
To produce the results needed to conduct a thorough study, a CNC 3-axis vertical machining
centre was used. The Mazak Vertical Center Smart 430A (MVCS) as seen in Figure 7 was the
chosen machine as it is similar to those used by industry leaders today. The MVCS’s ability to
machine in 3 axes of direction enables the production of complex components and shapes,
this along with the maximum specified spindle speed being a very high 12000 rpm, allow for
a broad range in changing the cutting parameters. Another feature that made the MVCS a
suitable machine was its capacity to hold multiple tools at once. As complete testing of tools
could not always be done in one sitting, it allowed the cutting tool to be left on the machine
Figure 7 - Mazak Vertical Center Smart 430A (image reproduced from Mazakusa.com, 2016).
Controller
Machine table
Protective
screen
Tool holder
20. 20
without having to be removed and refitted by a technician, which could have potentially
caused the tool to be positioned differently, affecting results.
Another feature of the MVCS is the CNC controller that operates it, the Mazatrol Matrix
Nexus 2. The controller allows for a CAD design to be uploaded to the machine, the design is
then converted into the machines Mazatrol programming language which then generates a
program of how it is going to cut the component, this program can then be viewed and
altered by the technician using the LCD display and controls.
4.2 Metrology methods
Tool wear can be measured in multiple ways, these different methods can be categorised by
whether they are direct or indirect and also by whether they are in-process or post-process.
Traditionally tool condition is monitored using the direct post-process method of observing
the tool through a microscope after cutting. This process has been very popular as in its
simplest form it only requires a toolmakers microscope fitted with a measuring scale. The
area of flank wear (also known as flank wear land) is observed through the microscope and
then measured. Recent investigations (Samik et al. 2016) involving the use of optical
methods to indirectly measure tool wear have attempted to predict a single point turning
tool’s flank wear by illuminating the machined surface and recording the brightness of the
reflection. The theory being that as flank wear increases the roughness of the machined
component will also increase and will therefore shine brighter due to an increased
scattering of light. A positive correlation was found between the increase in the intensity of
reflected light and the flank wear land measured, proposing it as a possible method of tool
21. 21
condition monitoring. However the tests all had to be carried out with exactly the same
intensity of aperture and ambient lighting, making it impractical for use in industry.
Another direct post-process method of monitoring tool wear is measuring machined part
dimensions. Comparing dimensions of sequential machined components allow a user to
gauge the change in dimensions of the cutting tool and the direct effect on what it
produces. This is often manufacturers preferred method of quality control as variables
affecting dimensions such as temperature change throughout the measurement process can
be compensated for, meaning it can therefore be carried out on the shop floor. Another
bonus to this method of metrology is the ability to measure the changes in geometry of the
tool, not just its diameter. However the changes in diameter can only be recorded after the
component is machined and accurate equipment such as a CMM can be costly, this
alongside the reality that the process of measuring components takes up time that could be
spent machining mean that this method is often also seen as non-productive.
In-process measures of tool wear record wear during the machining process, potentially
allowing for real time changes in tool offsets. Vibration analysis (Wojciechowski et al. 2014)
as mentioned earlier and also tool force analysis are indirect in-process methods of tool life
monitoring. An automatic tool management systembased on tool force analysis has already
been proposed (Denkena et al. 2014). The systemuses the findings of a linear correlation
between tool force amplitudes and tool flank wear to monitor tool condition. Using this
information the system can then vary spindle speeds based on the values of cutting forces
recorded at dynamometers attached to the machine shaft.
For this project it was decided to use the method of measuring the dimensions of the
machined component. The reasons for this were that the measurement machines were
22. 22
already available in the lab and it’s similar to how industry currently tends to conduct
quality control and is therefore relevant to current practices. However not having the
pressures of productivity and profit that are experienced in industry mean that testing can
be done more thoroughly. Time constraints and the availability of equipment also ruled out
other methods, however a future direction for investigations would be an in-process
method of tool wear measurement such as force analysis as the MVCS has the ability to
measure spindle forces and this has the potential to be an integral part of future industries
and their tool condition monitoring.
4.3 Coordinate measuring machine (CMM)
Figure 8 - Image of Mitutoyo Euro-C-A121210 CMM.
Component for movement in
Z direction
Component for movement in
Y direction
Motorised indexing head
Stylus probe
Dedicated calibration sphere
Component for movement in
X direction
CMM controller
23. 23
The CMM used to measure the component geometries was a Euro-C-A121210 produced by
Mitutoyo pictured in Figure 8. The design of the CMM consists of a probe attached to the
vertical component which is attached perpendicularly to a bridge structure. This bridge
structure is in turn attached perpendicularly to a large granite bed. Air bearings along each
component allow for smooth independent movement along the X, Y and Z directions. The
stylus probe is mounted to a motorised indexing head which in turn is mounted to CMM
structure as can be seen in Figure 8. The motorised indexing head can rotate about two
more axes, allowing for the probe to be position in varying angles. When the stylus at the
end of the probe comes into contact with an object, an impulse is sent to the controller
leading to the recording of each components’ location along their relevant axes with a
precision of 7.5 nm. As the CMM is so precise, temperature can have an effect on its
accuracy. To avoid this the room in which the CMM is located is temperature controlled,
also the large granite bed has a high thermal mass to further ensure that changes in
temperature will not affect any gathered results.
4.4 Stylus probe
Kinematic mounting
Strain gauge
Stylus
Figure 9 - Inner construction of a strain gauge probe (image reproduced from plc, 2016).
24. 24
The Renishaw strain gauge stylus probe attached to the CMM consists of a stylus probe that
is mounted to the body of the probe kinematically. Kinematic mounting involves designing
the body and stylus of the probe so that the stylus can only locate one way, this ensures it
will always return to the same neutral position after it has been unseated, providing
repeatability. A series of strain gauges arranged around the stylus and attached to the body
of the probe as in Figure 9 enable the measurement of the forces unseating the stylus from
the probe body when the stylus comes into contact with an object. This signal is then sent
back to the controller and recorded. The strain gauge system and body is encased in a
protective housing to stop the interference of particulate matter. The reason for not using
simply a kinematic resistive probe was that a kinematic resistive probe can only record the
position at which the stylus is unseated from the body whereas a strain gauge systemallows
for a constant reading of force to be measured, enabling the measurement of dimensions
such as circularity.
4.5 Cutting tool and test piece material
The test pieces were each cut to a length of 220mm from the same length of bright mild
steel 125mm wide by 25mm thick. Although it was impossible to completely remove the
occurrence of variations in the composition of the steel, taking cuts from the same length
should have reduced the occurrences.
Bright mild steel is a cold drawn low carbon steel that is often used in metal cutting
processes, particularly milling. Mild steel is classified by a carbon content lower than 0.25%
with no other alloying elements in its makeup. Bright steel is steel that has been cold drawn
25. 25
through a die, this increases its mechanical properties of hardness and also tensile and yield
strengths. Bright mild steel has a higher machinability rating than mild steel and also high
carbon steels enabling cutting processes to be run at higher cutting speeds and feeds while
maintaining a good surface finish. This is better than mild steels
because the increased mechanical properties stop the material from
sticking to the cutter when machining at higher speeds. This sort of
steel is also more machinable than high carbon steels as the carbides
in high carbon steels abrade the cutting tools.
The cutting tool chosen pictured in Figure 10 was a high speed steel
(HSS), 16mm diameter, 4 flute end mill. Although modern day industry
uses cemented carbide inserts far more than HSS cutters, HSS was
chosen for the following reasons:
1. The expected tool life of HSS cutters when milling bright mild steel is considerably
lower than carbide inserts, which are much harder. This meant that tests could be
conducted in a shorter space of time, reducing the risk of procedural errors and
interruptions.
2. Cemented carbides are attached as tips to larger tools, increasing the opportunity
for variation in the attachment of each tip. Alongside this there is also the issue that
as these tips are so small, often around 5mm across, measuring the change in
geometry across the tip would not be possible with the CMM and probe
configuration.
Figure 10 - HSS
cutting tool.
26. 26
3. An HSS end mill is more versatile, this means it is capable of plunging directly into
the workpiece as well as milling slots across it. This is in contrast to tools using
carbide inserts which often have very specific roles, such as face milling or boring.
Given the tool and workpiece material the recommended cutting speed can be obtained
from a machinists’ handbook, for the specified cutter workpiece combination the
recommended value is 36m/min. Gathering values of n and C displayed in Table 1, it is now
possible to determine a predicted tool life using equation ( 5 ). At this point it is not possible
to use one of the extended equations ( 8 ) or ( 10 ) because of the lack of experimental
constants a and b.
Table 1 - Values of n and C for a HSS cutter milling carbon steel.
Possible value of n Typical value of n Possible value of C
(m/min)
Typical value of C
(m/min)
0.125 – 0.20 0.125 40-100 70
Using the typical values of n and C, a tool life (T) of 204.3 minutes is obtained. However,
when using other possible values in Table 1 it is possible to see that the predicted tool life
ranges from 3544.7 minutes to 1.69 minutes. Also of note is this theoretical tool life is the
predicted time it takes for 3µm of flank wear land to be observed, not to tool failure. In
order to gain complete tool failure the test must involve more cutting time than this.
4.6 Test piece design
In order to be able to measure the changes in diameter across the tool’s length, a depth of
cut (y) of 5mm was selected. This depth is deep enough for the probe to be able to
27. 27
distinguish between separately cut areas but not too deep to adversely affect wear.
Inputting the values of Vc and y into equation ( 1 ) determines the spindle speed (N):
( 11 )
( 12 )
The chosen cutter and workpiece material also has a recommended feed per cut (fn) of
0.25mm/rev. Rearranging equations ( 2 ) and ( 4 ) and substituting in the previously found
values, the maximum metal removal rate (Q) for a 16mm cutter can be found:
( 13 )
( 14 )
Using the information for Q and the calculated predicted tool life of 204.3 minutes, suggests
the tool would remove 2927.6cm3 of material before the end of its life. In reality it would
not be this much as changes in the diameter of the tool would reduce the amount of
material removed.
Further considerations of the design of the test piece were how repeatable each cut was in
order to be able to compare them. In order to achieve this cylindrical shaped cuts were
chosen. Although a cylindrical shape necessitates a more complex cut pattern involving
28. 28
overlaps than for example a cube, it allows for simple measures of diameter as well as the
opportunity to observe the effects of wear on circularity. Other requirements of the test
piece were that it needed to enable the measurement of surface roughness for further
investigations into the effects of tool wear.
Figure 11 is a representation of the image that was uploaded to the MVCS and the CMM.
There was strip 0.5mm deep at one end that was to be cut first in order to provide a
reference point for the top of the workpiece. The slots for surface roughness ran through
the middle of the piece and were milled in sections after each hole. For example after
boring the first 40mm x 20mm hole the tool would then mill a section of the slot and then
the process would repeat.
The theoretical volume of metal to be removed by the milling process was 218.4 cm3,
requiring 14 test pieces to reach the tool with the optimum cutting parameters tool life.
1
2
3
5
4
6
8
7
b
a
c
d
e
f
g
h
0
Reference plane:
0.
Holes:
1, 2, 3, 4, 5, 6, 7, 8.
Surface finish slots:
a, b, c, d, e, f, g, h.
Cutting order:
0, 1, a, 2, b, 3, c, 4, d, 5,
e, 6, f, 7, g, 8, h.
Figure 11 - CAD drawing of test piece and cutting order.
29. 29
However, due to the possible range of values of tool life, it was not expected to take this
long. Furthermore subsequent tool tests were to be run at higher cutting speeds to gain
information on the effects of higher speeds
4.7 Expected Outcome
The expected outcomes of the tests were to find evidence of more wear when the cutting
speed was higher as calculations using equation ( 5 ) and pre-existing knowledge provide
evidence that a tool’s life is reduced when operating at higher cutting speeds.
A further prediction was that the tools’ would wear in sections along their length, so the
diameters would change along their length, creating a similar profile to what is seen in
Figure 12.
Cylinder 2
Cylinder 1
Cylinder 3
Cylinder 4
Cylinders:
1 = 2 = 3 = 4 = 5mm
Workpiece
B
A
C
D
Sections:
A = B = C = D = 5mm
Tool tip
Tool
Top of workpiece
Bottom of hole
Hole and tool
centreline
Figure 12 - Expected outcome of tool and part geometry. (Not to scale).
30. 30
The general understanding in the industry is that a more worn tool will cause circular shapes
to go ‘out of round’. However not many definitive previous scientific studies or information
could be found on the effects that wear would have on circularity during a milling operation.
An investigation by Kivak et al. (2012) found that increases in cutting speed during drilling
had no effect on circularity, however increases in feed per cut would make the drilled holes
less circular. It was suggested that there could be a similar effect seen during a milling
process, however the cutting forces present in a drilling operation are enacted in a different
direction during a milling operation.
31. 31
5 Testing process
5.1 Cutting operation
All of the testing process was carried out by a technician who was experienced and trained
to use the machine safely.
To begin testing a brand new tool was first fixed firmly in the tool holder of the machine, the
tool had to be firmly tightened into the holder in order to prevent loosening which could
lead to the tool moving in its holder and voiding results. Similarly the work material was
fixed firmly into the work holder on the machine table. Each successive test was then fixed
exactly the same way.
The CAD file was then uploaded to the CNC controller along with the information relating to
the tool and workpiece materials and also cutting speed and depth. From this the controller
then set the optimum feed per cut and calculated the other cutting parameters. The
controller also generated the cut path it would follow. The first cut to be made was the strip
at one end of the test piece for the reference plane. The next cutting operation was for hole
A
B
C
A = 16mm
B = 8mm
C = 4mm
Figure 13 - Diagram of tool cutting operation of a
hole with cut widths.
32. 32
one, from Figure 13, this was to start with an initial plunge into the centre of the workpiece
down to 5mm depth. After this the cutter would then proceed to open out the initial bore
by a radius increase of 8, once finished with this procedure the cutter would then move
directly to the final radius and cut the remaining 4mm width left surrounding the cylinder.
From there the process would then start again to bore out the next cylinder down until four
of these cycles had been complete. As seen in Figure 11, the cutter would then proceed to
machine the first surface finish slot. After this the whole process was repeated until 8 holes
and slots were machined.
Once the test process was set up the protective screen was closed (Figure 14) and the
machining process started.
The time it took the machine to cut one test piece was roughly 20 minutes, however this
varied depending on the different cutting speeds and diameters of the tools. Notable
throughout the cutting of each test piece was the feed per cuts changing for each different
Figure 14 - Machine during a cutting process.
33. 33
cut, increasing the variation throughout the process. Once a test piece had been completed
(Figure 15) the operator could then open the protective screen and remove it from the work
holder before fixing in a new piece of material. In order to increase the repeatability and
reliability of the tests only one work holder was used throughout all the testing processes
and during testing it was not moved from the machine. Testing for each tool carried on in
this way until the technician deemed from their own experience that the tool had worn out,
at which point the tool was removed.
5.2 Measurementoperation
In order to operate the CMM the CAD design was uploaded to the CMM’s controlling
computer. From the uploaded file a programme could be created using the CMM’s
programming language that recorded the geometries of the design in order for the CMM to
reference them when operating. A program was then created that enabled the CMM to
measure the required geometries.
Figure 15 - Image of completed test piece 16.
34. 34
The finished workpiece was fixed to a holder that allowed for it to be positioned only one
way, this meant that sequential tests would also be located in the same position each time.
This holder was then placed on the granite bed of the CMM ready for the measurement
process to begin.
The measurement process began with the operator using the joystick on the controller to
manoeuvre the tip of the probe to follow the commands detailed in Figure 16. The reason
for this initial operation was for the CMM to locate its data points, enabling it to find the
part. The heading at the bottom of Figure 16 ‘$$ CNC Alignment $$’ signals the beginning of
the CMM’s auto alignment, where it determined more accurately where each part of the
test piece is in reference to the CAD design uploaded to it.
The next stage was the actual measurement process of the cylinders in the holes. The probe
first moved to the coordinates above the hole to be measured, then proceeded to lower
into the hole. Each 5mm deep cylinder had three points about its circumference taken to
determine its diameter, then the tip of the probe ran around the circumference to
determine the circularity. After each cylinder was completed the next cylinder 5mm down
was measured for a total of 4 cylinders per hole. The final measurement in each hole was to
Figure 16 – CMM commands to user to establish alignment of the test piece.
35. 35
gauge the distance from the bottom of the hole to the reference slot. Once completed for
all 8 holes the measurements were outputted to an excel file in the format of Figure 17 so
the data could be analysed. Using the data for diameter and making the assumption that a
new tool has a perfectly consistent cross section along its length, the wear was determined
by subtracting each following cylinder’s diameter from the diameter of ‘Hole 1 Cylinder 1’ of
the first test piece of each tool. In reality even a brand new tool does not have exactly the
same cross section along its length, so this method of calculating wear is not accurate for
determining magnitude of wear, however it provides an opportunity to compare the rates at
which different sections of the tool wear.
Figure 17 - Sample of excel file for test 4.
36. 36
6 Results and analysis
6.1 Cutting conditions
Before each test the condition of cutting speed was set, the optimum feed per cut for the
particular tool was then chosen by the CNC machine. The parameters of table feed, spindle
speed and metal removal rate could then be calculated. Once the tool was fitted in the
holder on machine probing was used to determine the initial tool length and the tool was
then not removed from the holder until the end of testing, in this way reducing the chance
of a procedural error that could occur from refitting the tool and potentially affecting any
gathered results.
Table 2- Cutting conditions and initial tool dimensions for each tool and the order the tests
were completed in.
Tests Tool
Number
Vc
(m/min)
fn
(mm/rev)
Vf
(mm/min)
N
(rev/min)
Tool
Diameter
(mm)
Maximum
Q
(cm3/min)
4,5,6,7,8 3 36 0.25 179.1 716.2 16 14.33
9,10,11,12 4 43 0.25 214 856 16 17.12
13,14,15,16 5 52 0.25 258.7 1035 16 20.70
2.1,2.2,2.3 2.1 52 0.17 281.5 1656 10 14.08
The conditions for the initial tests, the same as those in tests 4 to 8 seen in Table 2, were
selected by taking the recommended cutting speed for a milling operation involving a high
speed steel cutter and bright mild steel workpiece found in machinists handbooks, and
inputting that to the CNC machine. The machine then set the feed per cut that would lead to
the optimum cutting process for decreased tool wear by taking into account the
37. 37
machinability of the material, the number of teeth on the cutter and also the cutter
diameter. The cutting speeds for tests on subsequent tools were increased from the initial
tests, with the exception of tests on tool 2.1 where the diameter was decreased, the
explanation for which is detailed later in the report.
The initial tests 1, 2 and 3 were carried out on tools 1 and 2 however the results are not
included as changes in the design of the test piece for use in another project meant the
tests were interrupted part way through, leaving incomplete results.
6.2 Tool 3: Tests 4, 5, 6, 7, 8.
Tests 4 to 8 were carried out on tool 3 under the optimum cutting conditions for extending
tool life, it was still expected that the tool would deteriorate and wear before failing.
-0.02
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
0.2
0.22
0.24
0.26
0.28
0.3
0.32
0.34
0.36
0.38
0.4
0.42
0.44
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40
Wear(mm)
Hole number
A B C D
Figure 18 - Wear of tool 3 throughout tests 4 to 8.
38. 38
In Figure 18 it is possible to see the initial wear taking place between the start of testing and
the second cut hole by the steep positive gradients in each of the four measured sections of
the tool. After this stage of initial wear the plots for each section increase at constant rates,
indicating that the tool has entered the uniform wear stage. Excluding the repeating
anomaly that can be seen occurring in the 3rd hole of every test piece (holes 3, 11, 19, 27
and 35), and the abnormally low results recorded for holes 33 and 34, straight trend lines
can be fitted to each in order to determine the rate of wear for each section of the tool per
hole during this uniform wear stage.
Table 3 - Wear rate at separate sections of tool 3.
Section of tool Wear rate (mm/hole)
A 1.0×10-3
B 1.4×10-3
C 1.4×10-3
D 1.4×10-3
The results in table 2 show the same rate of wear occurred in sections B, C and D at 1.4×10-3
mm/hole. The lowest rate of wear was 1×10-3 mm/hole at A, showing that the wear that this
area was subjected to altered its dimensions much less than the areas of the tool that had
more contact with the workpiece. The absence of an increase in gradient towards the end of
the results is evidence that the tool had not yet failed.
The circularity results for tool 3 displayed in Figure 19 show similar trends to those of the
wear shown in Figure 18. A steep initial gradient at the beginning of the testing again ending
at hole 2 is followed by a much smaller positive constant gradient which again, does not
39. 39
increase. The highest and lowest values occur in cylinder 4 and cylinder 1 respectively in
both Figure 19 and Figure 18, suggesting a link between the quantity of wear the tool has
undergone and the component circularity. The recurrently high results for wear in holes 3,
11, 19, 27 and 35 are replicated in the circularity, with a large set of values being 0.3 mm
larger than expected. Furthermore, the very low results for circularity and wear seen for the
values of holes 33 and 34, suggest it can be assumed that the variations have occurred
during the machining process as opposed to errors during the measuring process or the
presence of wear. The justification for this is the circularity and the diameter of the cylinders
are recorded in separate processes, meaning an error in the measurement of the circularity
would not be expected to correspond with an error in the measurement of the diameter,
which the value for wear is derived from.
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
0.2
0.22
0.24
0.26
0.28
0.3
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40
Circularity(mm)
Hole number
Cylinder 1. Cylinder 2. Cylinder 3. Cylinder 4.
Figure 19 - Circularity of the holes in tests 4 to 8.
40. 40
6.3 Tool 4: Tests 9, 10, 11, 12.
As a result of the failure stage not being reached in the previous tests and knowledge that
an increase in cutting speed has a negative effect on the length of tool life (Yan et al. 2009),
it was decided to increase the cutting speed for testing on tool 4. The increase in cutting
speed was expected to reduce tool life to the point where the failure stage of the machining
process could be observed at some point in the duration of testing. However the lack of an
increase in gradient of the graphs after the steep initial increase shown up to hole 1 in
Figure 20 is evidence that the tool has not reached its failure point and still has useable life.
The highest rate of wear during the uniform wear stage is 1.6×10-3 mm/hole seen in D. Only
marginally higher than 1.4×10-3 mm/hole recorded in B and C, it is evidence that the final 5
mm section of the tool that would have removed the largest quantity of material, was
wearing slightly faster. Similarly to tool 3, section A of tool 4 also experienced the lowest
Figure 20 – Wear of tool 4 throughout tests 9 to 12.
-0.04
-0.02
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
0.2
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32
Wear(mm)
Hole number
A B C D
41. 41
rate of wear at 0.8×10-3 mm/hole, 0.6×10-3 mm/hole less than B and C and half the rate of D.
This means the diameter of tool 4 at section A would be reducing at a much slower pace
over the course of its lifetime compared with the other sections. Referring back to Figure 18,
sections B, C and D of tool 3 experienced the same uniform rate of wear as sections B and C
of tool 4, showing that the change in cutting speed was not great enough to be able to
distinguish between the two sets of results.
The circularity results obtained from tests 9 to 12 are displayed in Figure 21. Similarly to the
circularity results for tool 3, the circularity degrades for each consecutively deeper cut, with
the exception of a minority of the results. This is shown in Figure 21 by circularity increasing
each section in the majority of holes from cylinder 1 to cylinder 4 throughout the tests. This
corresponds with a similar trend of wear increasing for each section towards the tip along a
tools length. The extremely high value of circularity seen for cylinder 4 in hole 13 does not
0.12
0.14
0.16
0.18
0.2
0.22
0.24
0.26
0.28
0.3
0.32
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32
Circularity(mm)
Hole number
Cylinder 1. Cylinder 2. Cylinder 3. Cylinder 4.
Figure 21 – Circularity of the holes in tests 9 to 12.
42. 42
correspond with a high result for wear at the same hole in section D, suggesting an error
occurred during the measurement of this result. A possible cause of this variation is a piece
of material obstructing the probe and affecting the results, another measurement of the
hole would be needed to confirm this.
Representing the results from Figure 21 as straight trend lines, it is possible to see the
difference in the rate of degradation of circularity. In Figure 22 the rate of change in cylinder
4 is the greatest at 0.7×10-3 mm/hole and then slightly less in cylinders 2 and 3 at 0.5×10-3
mm/hole. This is a similar set of results to those seen for wear along sections B, C and D of
tool 4. The rate of change in circularity is a small decrease of -0.08×10-3 mm/hole, so small
that it can be considered that the wear experienced by section A of tool 4 was too little to
have any noticeable impact on the circular geometry of the hole.
0.14
0.15
0.16
0.17
0.18
0.19
0.2
0.21
0.22
0.23
0.24
0.25
0.26
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32
Circularity(mm)
Hole number
Linear (Cylinder 1.) Linear (Cylinder 2.) Linear (Cylinder 3.) Linear (Cylinder 4.)
Figure 22 – Linear plots of circularity for tests 9 to 11.
43. 43
6.4 Tool 5: Tests 13, 14, 15, 16.
Due to previous tests not reaching the failure stage, cutting speeds were increased to 52
m/min while maintaining the same depth of cut and feed per cut. The expected outcome
was for this to sufficiently increase the rate of wear of the tool to cause it to fail. The rates
of increase in wear of each section after the initial wear stage, which can be seen in Figure
23, are constant throughout the testing period, this is evidence that the tool again did not
fail. The rates of wear of all the sections has increased on previous tests, corresponding with
the increase in cutting speed. However conversely to previous tests, the greatest increase in
wear is seen in section A at a rate of 2.7×10-3 mm/hole. This is higher than rates of B, C and
D which were 2.1×10-3 mm/hole, 2×10-3 mm/hole and 2.5×10-3 mm/hole respectively. Why
the biggest rate of wear is seen in section A is not fully known, however a suggestion is the
high table feed causes higher tool deflection (Saffar et al. 2009) the deeper the tool is
cutting, this displacement in turn reduces the feed per cut of section A in relation to the
-0.04
-0.02
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
0.2
0.22
0.24
0.26
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32
Wear(mm)
Hole number
A B C D
Figure 23 – Wear of tool 5 throughout tests 13 to 16.
44. 44
cutting speed leading to a higher rate of wear. Comparatively with previous tests, sections B
and C again experienced similar rates of wear to each other.
The circularity of tests 13 to 16 in Figure 24 produced results that followed few trends
identified in previous tests. For example there is no obvious difference up to hole 18
between the circularities of cylinders 2, 3 and 4. After this point it can then be seen that the
circularities start to differ with cylinder 1 having the lower values and cylinders 2, 3 and 4
increasing in order, similar to what can be seen in Figure 21 and Figure 19. In terms of the
values, most of the results are between the range of 0.14 mm to 0.24 mm, which is similar
to what was seen in previous Figure 21 and Figure 19, showing that the increase in the
cutting speed has not had a negative effect on the circularity.
0.12
0.14
0.16
0.18
0.2
0.22
0.24
0.26
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32
Cylinder 1. Cylinder 2. Cylinder 3. Cylinder 4.
Figure 24 – Circularity of holes in tests 13 to 16.
45. 45
6.5 Tool 2.1: Tests 2.1, 2.2, 2.3.
As the successive increases in cutting speed had not been able to produce results that
represent all the stages of tool wear, the decision to reduce the diameter of the cutting tool
to 10 mm was made. Reducing the diameter of the cutting tool was expected to increase
the amount of wear recorded by reducing the area of the tool engaging the workpiece,
while still maintaining the same amount of material to be removed, thus the tool will
remove more material per cutting area. In theory, not taking into account the diameter
changes due to wear, over the final 20 mm length of the tool this reduces the area exposed
to the workpiece from 1206.34 mm2 to 706.86 mm2, through the duration of one test piece
this increases the material removed per area of the tool from 251.90 mm to 429.90 mm.
Looking at the wear experienced by tool 2.1 in Figure 25, it is possible to see the rapid wear
stage occurring, represented by an increase in gradient of the graphs beginning at hole 16.
-0.1
-0.06
-0.02
0.02
0.06
0.1
0.14
0.18
0.22
0.26
0.3
0.34
0.38
0.42
0 2 4 6 8 10 12 14 16 18 20 22 24
Wear(mm)
Hole number
A B C D
Figure 25 - Wear of tool 2.1 throughout tests 2.1 to 2.3.
46. 46
The presence of rapid wear means the tool has reached the end of its useable life and the
condition of the tool would carry on deteriorating at an increasingly higher rate if used
more. Also present in Figure 25 are the stages of initial and uniform wear. Modelling the
data from hole 1 to 16 as straight lines as in Figure 26, it is possible to see the rate of
increase in wear throughout the uniform stage for the sections A to D, which are: 2×10-3
mm/hole; 3.5×10-3 mm/hole; 4.9×10-3 mm/hole and 5.3×10-3 mm/hole. These results are an
increase on previous values in Figure 18, Figure 20 and Figure 23 for the same stage,
showing a positive link between the amount of material removed per engagement area of
the tool and the amount of wear experienced.
These results are in line with the expected outcome of rate of wear, with the lowest being
seen at A and then increasing each section to the highest rate of wear at D. This period of
uniform wear is followed by a period of rapid wear, where the biggest increase is seen in D
from 5.3×10-3 mm/hole to 20.3×10-3 mm/hole.
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
0.2
0.22
0.24
0.26
0 2 4 6 8 10 12 14 16
Wear(mm)
Hole number
Linear (A) Linear (B) Linear (C) Linear (D)
Figure 26 - Uniform wear stage of tool 2.1 modelled as straight lines.
47. 47
Similarly to what was seen in the wear of previous tools, the largest value at each hole can
be seen in section D with C, B and A decreasing in that order, suggesting again that the
dimensions of section D have been altered the most, followed by the others in increasing
order of distance from the tip of the tool. Where Figure 25 differs from Figure 18, Figure 20
and Figure 23 is that the smallest difference in the amount of wear is observed between B
and C rather than C and D.
The uniform and rapid stages of wear observed in Figure 25 can also be seen happening
concurrently in the circularity shown in Figure 27. The uniform stage is evident up to hole 16
with a small positive gradient, after which the gradient changes and rapid wear begins,
further evidence that the tool had reached the end of its useable life.
The values of wear and circularity at hole 20 for the tests on tool 2.1 (Figure 25 and Figure
26) are much lower than would be expected. For reasons mentioned previously, because
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
0.2
0.22
0.24
0.26
0.28
0.3
0 2 4 6 8 10 12 14 16 18 20 22 24
Circularity(mm)
Hole number
Cylinder 1. Cylinder 2. Cylinder 3. Cylinder 4.
Figure 27 - Circularity of holes in tests 2.1 to 2.3.
48. 48
similar errors are observed in both the circularity and the wear, it is likely that the variation
occurred during the machining process as opposed to an error in measurement.
6.6 Analysis of results
All the gathered results showed the biggest changes in diameter from the first cut to each
sequential cut occurring in cylinder 4, at the bottom of each hole. Due to the repeated
result, this is evidence that the greatest amount of wear is occurring in the final 5mm of the
tool, leading on to the assumption that the tool geometry here is being changed more than
other sections and its dimensions are no longer uniform. It is also noticeable that evidence
of wear decreases successively each section back from the tool tip, showing the tool is
wearing in a stepped conical fashion. Furthermore, it can be seen in all tools with the
exception of 2.1 that had reached its failure point, that the difference between the amount
of wear occurring at each section of the tools is smallest between section D and C, then
B
A
C
D
δ1
δ2
δ3
A = B = C = D = 5mm
δ1 > δ2 > δ3
Tool tip
Figure 28 - Exaggerated profile of suggested final shape of tool flank. Not to scale.
49. 49
increases between C and B and is the greatest between B and A. This suggests that the final
shapes of these tools may be similar to what is seen in Figure 28. Because the difference in
wear between sections did not seem to increase in a way that related to the increases in
cutting speed in the data, it is not possible with these results to mathematically model the
way cutting speed affects the creation of the steps.
The increase in cutting speed’s effect on tool wear is most prominent in the end 5 mm of
the tools. Calculating the increase of wear at this area during the uniform wear stage for
each tool by plotting the change in diameter from the start of the uniform stage (hole 2)
such as in Figure 29, it is possible to see how the increase in cutting speed affects the
change in wear. Looking at the tools of 16 mm diameter, tool 5 that operated at the highest
cutting speed of 52 mm/rev recorded the biggest increase in wear, roughly double that seen
in tools 3 and 4 over the same period. Also observable is how similar the increases are
between tools 3 and 4 despite tool 4 having the higher cutting speed of 43 mm/rev
compared to 36 mm/rev. As a result of this from the gathered data it is not possible to
-0.02
0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
0.16
0.18
0.2
0.22
0.24
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32
Wear(mm)
Hole number
Tool 3 (16mm) Tool 4 (16mm) Tool 5 (16mm) Tool 2.1 (10mm)
Figure 29 - Increase in wear of the final 5 mm section of the tools from the beginning of the
uniform wear stage.
50. 50
reliably say that cutting speed increased the wear, however it is well known that in fact it
does. The biggest increase in wear was seen in the tool with the 10 mm diameter, tool 2.1.
As cutting speed was kept the same as in tool 5, it’s possible to say that a decrease in tool
diameter has a greater effect on wear when cutting the same volume of material.
It can also be observed that the cut holes became less circular as wear increased. This
suggests that deflection of the tool occurred. Deflection is a result of unbalanced forces
acting on the tool, this along with the knowledge that tool forces increase with wear (P.
Kolar et al. 2015) there is a viable connection that tool wear has a negative effect on
component circularity.
From the data produced, it is possible to calculate the experimental values of the Taylor
constants n and C by using the wear rates of tools 4 and 5 which are 1.6µm/hole and
2.5µm/hole respectively. Using the information for Vc and Q in Table 2, setting the tool life
as the period for the tool to experience 4µm of wear and knowing that the volume of
material removed for each hole and slot is 27.3cm3 allows the following calculations:
Tool number: 4 5
Holes before end of
tool life:
4
1.6
= 2.5
4
2.5
= 1.6
( 15 )
Material cut (cm3): 2.5 × 27.3 = 68.3 1.6 × 27.3 = 43.7 ( 16 )
Tool life (mins): 68.3
17.1
= 4
43.7
20.7
= 2.1
( 17 )
51. 51
After gaining the value of tool life, it is then possible to calculate the values of n and C using
equation ( 5 ):
Equations equal to C: 𝑉𝑐4 𝑇4
𝑛
= 𝑉𝑐5 𝑇5
𝑛
( 18 )
Substitute in values: 43 × 4 𝑛
= 52 × 2.1 𝑛 ( 19 )
Take natural logarithms: 𝑙𝑛43 + 𝑛𝑙𝑛4 = 𝑙𝑛52 + 𝑛𝑙𝑛2.1 ( 20 )
𝑛 = 0.3 ( 21 )
Substituting in to ( 5 ): 𝐶 = 65𝑚𝑚/𝑟𝑒𝑣 ( 22 )
Assumptions made in these calculations were that Q and the diameters of the holes stayed
constant. In reality this was not the case. The value for n lies outside the range of typical
values of n found in Table 1, suggesting it’s not correct. However, the experimental value for
C is very similar to the value found in Table 1.
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7 Conclusion
The object of the project was to design a repeatable test that would enable the
determination of different cutting parameters effects on tool condition. The design of the
test piece meant it was very repeatable and easily measurable with the use of a CMM. Also
to note is that it was possible to observe the change in tool geometries through diameter
and circularity changes in the test pieces. The tests found that in most cases as wear
increased the components became less circular. This is evidence of tool deflection which is
known to occur as wear increases due to cutting forces also increasing with wear. This
deflection meant it was not possible from the tests to accurately quantify the diameter
changes in the tool wear, but the changes in diameter did showed considerable evidence
that the wear experienced by the tools changed their geometry into an increasingly stepped
profile.
The cutting parameters never stayed constant throughout a process due to the CNC’s ability
to calculate the ideal feed per cut for each cut while it was operating. The force
dynamometers linked to the CNC would also cause the machine to slow its’ cut if the forces
became too high in order to protect machine parts. This variability in the cutting meant
actually attributing the wear to specific cutting conditions was not possible.
Industry applications of the results gained from the testing at this stage are limited.
However the usage of relatively small cut holes to determine tool wear could and is applied
by some manufacturers today. By designing the holes into an area where the material is
going to be machined from the component, it is possible to use on machine probing to then
gauge wear without incurring any material costs and minimal process costs.
53. 53
Further study in this area could involve using an in-process method of metrology such as
measuring the spindle forces. The CNC demonstrated its ability throughout the test to vary
its actions to suit different cutting situations, so better understanding of the effects of wear
on spindle forces would enable for the programming of the machine to react in a way that
would prolong tool life. This looks a promising method of tool management for the future as
the complexity and quantity of variations that occur during CNC machining, even between
CNC machines, make accurately predicting the effects of a process on tool wear very specific
and impractical.
54. 54
8 References
Crosby, P. 1979. Quality is free. New York: McGraw-Hill.
Denkena, B. Kruger, M. and Schmidt, J. 2014. Condition-based tool management for small
batch production. International Journal of Advanced Manufacturing Technology, pp. 471-
480.
Dutta, S. Pal, S. and Sen, R. 2016. On-machine tool prediction of flank wear from machined
surface images using texture analyses and support vector regression. In. Precision
Engineering 43, pp. 34-42.
Groover, M. 2011. Principles of modern manufacturing. Hoboken, N.J.: J. Wiley.
Kolar, P. Fojtu, P. and Schmitz, T. 2015. On Cutting Force Coefficient Model with Respect to
Tool Geometry and Tool Wear. Procedia Manufacturing 1, pp. 709-720.
Kunzmann, H. Pfeifer, T. Schmitt, R. Schwenke, H. and Weckenmann, A. 2005. Productive
Metrology – Adding Value to Manufacture. CIRP Annals – Manufacturing Technology, 54(2)
pp. 155-168.
Kivak, T. Habali, K. Seker, U. 2012. The effect of cutting parameters on the hole quality and
tool wear during the drilling of Inconel 718. Gazi University Journal of Science 25(2), pp. 533-
540.
Liu, X. Machining Dynamics in Milling processes. 2009. In. Cheng, K. Machining Dynamics.
London: Springer-Verlag, pp. 167-231.
55. 55
Mazakusa.com. 2016. VERTICAL CENTER SMART 430A. [online] Available at:
https://www.mazakusa.com/machines/vertical-center-smart-430a/ [Accessed 26 Mar.
2016].
plc, R. 2016. Inspection probe technology. [online] Renishaw.com. Available at:
http://www.renishaw.com/en/inspection-probe-technology--32933 [Accessed 27 Mar.
2016].
Taylor, F. 1907. On the art of cutting metals. New York: American society of mechanical
engineers.
Wojciechowski, S. Twardowski, P. 2014. The influence of tool wear on the vibrations during
ball end milling of hardened steel. In. Procedia CIRP 14, pp. 587-592.
Yan, J. Murakami, Y. and Davim, J.P. Tool Design, Tool Wear and Tool Life. 2009. In. Cheng,
K. Machining Dynamics. London: Springer-Verlag, pp. 117-148.
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Cardiff School of Engineering
Appendix A – Record of project meetings
NAME...............................................STUDENT NUMBER........................................
SUPERVISOR...........................................................................................
TEACHING DISCIPLINE ……………………………………………..
Date of
meeting
Supervisor’s assessment of
progress
Actions by next meeting Supervisor
signature
