Influence of Selected Technological Factors on the Hole Quality During Reaming.
Fulemova, Jaroslava ; Kutlwaser, Jan ; Gombar, Miroslav 等
Influence of Selected Technological Factors on the Hole Quality During Reaming.
1. Introduction
Reaming is well known technology for producing precise and very
precise holes. The aim of reaming is increasing accuracy to shape and
accuracy to size. Reamed holes are produced with very tight tolerance
and with fine surface roughness. Generally, reamed hole can be produced
in grade of accuracy from IT 5 to IT8 and the quality of machined
surface up to Ra 0.4. Although reaming is finishing technology there can
be demand for more precise holes (lower than IT 5 and Ra 0.4), then it
is necessary to use the other technological operations like grinding,
rolling, honing, etc. [1], [2].
To produce precise hole means a number of technological operations.
First of all it is drilling. Accuracy grade of drilled hole is from IT9
to IT12, so it is roughing technology. After that it is boring or
chamfering. At the end is reaming. In every step of the production chain
is possible to make many mistakes which can influence accuracy and
quality of reamed hole.
1.1. Problem statement
A part of results, which are presented in this paper, can be found
in diploma thesis [3] and they belong to project Ro RTI A7. This project
is focused on determination of all factors which can influence quality
of reamed hole. The main idea of the project is based on basic research
whose results will provide information for practical application.
Results of literature research provide answer to a few specific problems
and give general information about geometry and function of reamers. But
nowhere is written which parameter influences the quality of reamed
hole. This article tries to determine factors which can influence hole
quality during reaming by using DoE (design of experiment) and at the
same time draw attention to weaknesses of experiment preparation.
1.2. Literature research
Bhattacharyya et al. [4] designed mechanistic model to predict
cutting forces for arbitrary reamer geometry. Input parameters for this
model are reamer geometry, feed rate, cutting speed, initial hole
geometry, process faults including parallel offset runout, spindle tilt,
respective locating angles and tool/hole axis misalignment. Mechanistic
model will predict torque, feed and radial force. The model valid over
range of feed rate, cutting speed and varying reamer geometry. Designed
model was validated by experiment. They found that parallel offset
runout, spindle tilt, spindle tilt locating angle, and tool/hole axis
misalignment have significant effects on the radial forces. These radial
forces are shown to be correlated to hole quality. [4]
Hauer et al. [5] investigated the influence of a diagonal
pre-drilled hole on hole quality during reaming using multi-blade tool.
Presumption of their research ware following. The varying input
parameters are influencing the width of cut and thus the quality of
reamed hole. Interaction between positional tolerance of pre-drilled
hole and the positioning accuracy of the machine tool lead to varying
depth of cut and thereby higher radial force. Finally reaming tool is
deflected and the hole quality worsens. They prepared experiment to find
out radial deviation of pre-drilled hole made by two different types of
drills. The results showed that smaller radial deviation has solid
carbide drill than drill with replacable head. After that this
pre-drilled holes were reamed to find out if the reamer follows
pre-drilled hole. This theoretical presumption was not validated. [5]
Towfighian et al. [6] observed the influence of low speed reaming
on vibrations of reamer with modified geometry. Designed FEM predict
vibrations. The lobbed of multi-cornered holes are formed during low
speed reaming. On the other hand tool chatter occurs at high speed
reaming. They found out that irregular spacing of 6 cutting edged leads
to perfect hole quality and the best combination of pitch angles also
leads to the most stable condition. [6]
Bezerra et al. [7] investigated the influence of cutting parameters
(depth of cut, cutting speed, feed rate, helix angle, number of blades,
margin size and rake face) on real diameter, roundness, cylindricity and
surface roughness during reaming aluminium-silicon alloy. They used
reamer with brazed cutting edges from sintered carbide K10. Conclusion
was following. Satisfactory hole quality can be achieved by smaller
values depth of cut, lower cutting speed, higher feed rate, straight
flute reamer with many blades and small margins. It is a paper which
describes the whole factors very deeply. [7]
Muller et al. [8] used DoE for set up parameters of reaming to
achieve parameters of machined surface and hole tolerance. They were
focused on three factors (spindle speed, feed rate and lubrication) on
two levels. As design of experiment was used full factorial experiment.
The results show that at small spindle speed, feed rate and lubrication
with oil the deviation of diameters is smaller than at high spindle
speed. When they used lower spindle speed, feed rate and oil lubrication
the surface roughness was lower than with higher parameters of cutting
process and lubrication with cooling lubricant at 1% concentration. [8]
2. Experiment
Experiment was done on turn-mill complete machining centre CTX beta
1250 TC 4A. As a workpiece was used a bar stock with diameter 30 mm and
length 550 mm. Final length of workpiece was 59 mm. The machine tool and
workpiece are in the Fig. 1. The bar stock was clamped into three-jaw
chuck and was made of 42CrMo4 steel. Chemical composition and mechanical
properties are in Table 1. This material is very often used for tool
holders.
2.1. Production process
There was used 6 blade reamer with brazed cutting edges from
cermet. The reamer was clamped into tool holder with possibility to
change eccentricity of the tool tip. This system is called Compensation
tool holder. Production process is in the Table 2.
2.2. Design of Experiment
To evaluate the influence of single factors on quality of reamed
hole there was chosen Central Composite Design with orthogonal blocking.
This type of experimental plan is possible to detect nonlinear relation.
The design of experiment takes into account 4 factors and every factor
has 5 levels. The main advantage of CCD plan is small number of samples,
to be specific 26 samples.
3. Experimental results
3.1. Cylindricity
Cylindricity of entire experiment were measured by Taylor Hobson
TalyRond 585 roundness and form measurement instrument. The measured
specimen was clamped in three-jaw chuck. Total measured height of the
cylinder is a bit smaller than reamed hole height, because the measuring
arm tip radius must be taken into calculation. Measuring arm with tip
radius 2 mm was used for measurement. The measured height was divided
into five levels and totally is the cylinder calculated from those five
cross-sections using Least squares method.
Our goal was to approve the influence of selected parameters on the
reamed hole cylindricity. We used a central composite design of the
experiment that allows finding a mathematical model, which describes our
response (cylindricity) in dependency on the process inputs, so called
factors--cutting speed, tool tip eccentricity, feed. The first step in
measured data evaluation, using mathematical model, is its creation by
for example regression analysis and then its evaluation. Model
suitability analysis is in Table 4.
We can see that the adjusted index of determination (Rsquare adj.)
is only 0.55 that means that our mathematical model cannot explain
approx. 44.5% of cylindricity variability. We can say that our selected
reaming process inputs have only 55.5% influence on the cylindricity
value. Let us have a look at model adequacy analysis, which was done by
ANOVA. The results are in Table 5. The probability smaller than
significance level (0.05) tells us that there is at least one
mathematical model parameter that has an influence on investigated
variable (in our case the cylindricity).
The next step in the model analysis is the Lack of fit test. (See
Table 6) This test proves us that the regression model perceives enough
the observed dependency. It tests that the variability of residuals in
comparison to variability of the values inside of groups. A null
hypothesis tells that the residuals variability is smaller or equal to
the variability of values inside of groups. The alternate hypothesis
tells us that the variability of residuals is greater than inside of
groups. The value of Fisher's test criterion is greater than
significance level (0.05) we can assume that we do not have enough of
evidence to reject null hypothesis. For us it means that our regression
model is sufficient.
We have sufficient and adequate regression model and now we can
calculate model parameters estimation (Table 7).
From Table 7 we can see several facts. Firstly, at 5% significant
level, the intercept has influence on the cylindricity value. This
represents all other factors that were considered as fixed or neglected,
or used factors intervals, other uncalculated errors etc. Next, other
factors that have statistical influence on the cylindricity value are
terms xi (cutting speed), [x.sub.2] (feed), [x.sub.3] (reverse feed),
combination of cutting speed and feed and at the end is the combination
of cutting speed, feed and reverse feed. What is interesting, the
eccentricity of the reamer does not have influence on the cylindricity
as independent factor neither as in combination with other factor. When
we have a closer look at percentage influence of factors on the hole
cylindricity, we can see that the intercept has 66%. The interaction of
cutting speed and feed 13%, interaction of cutting speed, feed and
reverse feed 9%, cutting speed has 3% of influence, feed influences the
cylindricity from 6% and the reverse feed has 3% influence on the
cylindricity.
At the end we have the prediction model of reamed hole cylindricity
converted to the real factors value:
Cyl = 207.519 x f + 0.865 x [v.sub.c] + 2.983 x [v.sub.f] - 1.187 x
f x [v.sub.c] - 4.174 x f x [v.sub.f] - 1.667 x [10.sup.-2] x [v.sub.c]
x [v.sub.f] + 2.322 x [10.sup.-2] x f x [v.sub.c] x [v.sub.f] - 143.628
(1)
For maximal complexity of regression analysis and selected
regression model validation, it is necessary to evaluate residuals
between measured and predicted values for their distribution and
autocorrelation. The autocorrelation of residuals was tested using
Durbin-Watson test and it showed us that there is no autocorrelation of
residuals. The normal distribution of residuals we tested by
Shapiro-Wilk test and it showed positive result for us, too. The model
residuals have normal distribution. By those two tests, we approve that
the model is statistically and numerically correct.
From analysis of regression model we can say that cutting speed as
independent factor does not have significant influence (at statistical
significance level 5%) on the reamed hole cylindricity. But, it is
significantly involved in several combinations with other factors, see
Fig. 3.
The feed rate has its own influence as an independent factor with
portion of 6%. It is also involved in interactions with cutting speed
and reverse feed rate. Graphical representation of this influence is in
Fig. 4.
3.2. Surface roughness Ra
Measured values of surface roughness reached very low deviation for
all 26 samples. Machined surface of reamed hole is possible to consider
as homogeneous. Surface roughness Ra was from 0.2 to 0.6 [micro]m. These
phenomena can be explained by material of cutting tool. High cutting
speeds, high feed rates and internal cooling are suitable for cermet
reamer. Under these conditions the reamer works more reliably.
3.3. Real diameter of reamed hole
previous experiment did not prove the influence of eccentricity on
cylindricity and surface roughness of reamed hole. So the new set of
experiments was done and its conditions are in the Table 8. There are
also values of real diameter which was measured at the top (D_up) and at
the bottom (D_down) of the reamed hole. These values brightly show, that
eccentricity of the tool tip does not influence quality of reamed hole.
Eccentricity has influence mainly on tool wear and on position error.
Clamping system is not perfectly stiff and overhanging of reamer is too
big. If the tool was shorter (lower overhanging), eccentricity would
influence measured parameters.
4. Conclusion
This article dealt with influence of four factors (cutting speed,
feed rate, reverse feed and eccentricity) on cylindricty, surface
roughness and real diameter of reamed hole. The reamed hole was blind
and was made by six blade reamer with brazed cermet cutting edges. The
tool wear was controlled and was not take into account. The experiment
proved that:
* the most significant component is constant. This constant
includes everything what was not take into account. It means, for
example, wrong range of cutting parameters; something what was changing
during the experiment and we did not know about it; something what we
could not influence, etc.
* main influence on cylindricity has feed, interaction of feed rate
and cutting speed and interaction between cutting speed, feed rate and
reverse feed. The higher feed rate and cutting speed the lower
cylindricity.
* experimental factors had not any influence on surface roughness
Ra. Cermet reamer proved produce homogeneous surface. It is because of
cutting material. Cermet is called "queen" of finished
surfaces.
* eccentricity did not influence the real diameter of reamed hole.
The main reason is stiffness of clamping system and overhanging of the
tool. At the first contact of the tool with the hole (chamfered part),
the reamer was led by drilled hole. If the reamer was shorter (lower
overhanging), we would suppose the bigger influence of eccentricity on
real diameter. Eccentricity has influence mainly on tool wear. The
higher eccentricity the lower tool life.
This experiment brightly proved that many factors has to be
controlled before experiment. Statistical methods design of experiments
can help us to find parameters which can influence the response and also
save out time and money. On the other hand we have to know very well
basic data, to understand the way of DoE, to know as much as possible
about relations between dependent and independent variable, to set up
right range of factors, etc. If we neglect something we will know it at
value of constant. If the constant is significant we can start again.
However, every mistake which we will do it, probably we will never
repeat it and this mistake will move us forward.
Future plans are based on results presented in this paper. So it is
necessary to choose right factors and their range. After that, we will
repeat the experiment and evaluate the data. Hopefully, we will be able
to express the influence of input parameters on the response.
DOI: 10.2507/28th.daaam.proceedings.046
5. Acknowledgement
The present contribution has been prepared under project LO1502
'Development of the Regional Technological Institute' under
the auspices of the National Sustainability Programme I of the Ministry
of Education of the Czech Republic aimed to support research,
experimental development and innovation.
6. References
[1] Fulemova, J. & Rehor, J. (2016). Reaming of very precise
and deep holes with cermet reamer. 27th DAAAM International Symposium on
Intelligent Manufacturing and Automation 2016, Volume 27, Issue 1, 2016,
Pages 275-282
[2] Klaic, M.; Staroveski, T. & Udiljak, T. (2014). Tool Wear
Classification Using Decision Trees in Stone Drilling Applications: A
Preliminary Study. 24th DAAAM International Symposium on Intelligent
Manufacturing and Automation 2014. Volume 69, Pages 1326-1335. DOI:
10.1016/j.proeng.2014.03.125.
[3] Roub, J. (2017). Influence of selected technological factors of
machining to surface integrity of precise holes--cutting conditions
during reaming. Plzen. Diploma thesis. ZCU v Plzni.
[4] Bhattacharyya, O.; Kapoor, S.G. & Devor, R. E. (2006).
Mechanistic model for the reaming process with emphasis on process
faults. International Journal of Machine Tools and Manufacture. 2006,
46(7-8), 836-846. DOI: 10.1016/j.ijmachtools.2005.07.022
[5] Hauer, T.; Haydn, M. & Abele, M. (2012). Influence of a
diagonal pre-drilled hole on hole quality during the reaming process
using multiblade tools. Journal of the Brazilian Society of Mechanical
Sciences and Engineering. Special issue 2, 2012, Vol. XXXIV, pp. 569-573
[6] Towfighian, S.; Behdian, K.; Papini, M.; Saghir, Z.; Zalzal, P.
& Beer, J. (2006). Finite element modeling of low speed reaming
vibrations with reamer geometry modifications. DOI: 10.
1007/s10845-007-0038-4.
[7] Bezerra, A. A.; Machado, A. R.; Souza, A. M. Jr. & Ezugwu,
E. O. (2000). Effects of machining parameters when reaming
aluminium-silicon (SAE 322) alloy . DOI: 10.1016/S0924-0136(01)00561-1.
[8] Muller, P.; Genta, G.; Barbato, G.; Chiffre, L. & Levi, R.
(2012) . Reaming process improvement and control: An application of
statistical engineering. DOI: 10.1016/j.cirpj.2012.07.005.
Caption: Fig. 1. Machining centre CTX beta 1250 TC 4A and workpiece
with twist drill and reamer
Caption: Fig. 2. Drawing of the sample
Caption: Fig. 3. Influence of cutting speed on cylindricity
Caption: Fig. 4. Influence of feed rate on cylidricity
Caption: Fig. 5. Influence of tested factors on surface roughness
Ra
Table 1. Chemical composition and mechanical properties of steel
42CrMo4
42CrMo4 Chemical C Mn Si P S
+ OT element
+ SH
% representation 0.43 0.85 0.19 0.021 0.020
Mechanical Rm [MPa] Rp 0.2 [MPa] A [%]
properties 1036 880 15.1
42CrMo4 Chemical Cr Mo Cu Al
+ OT element
+ SH
% representation 1.14 0.17 0.24 0.012
Mechanical Z [%] Kv [J] 20[degrees]C
properties 58 82
Table 2. Production process of the experiment
Nr. of operation 1. 2.
Technology Spot-drilling Drilling
operation
Dimension [mm] [??] 3 x 1.5 [??] 11.8 x 60
Material of the Sintered carbide Sintered carbide
cutting tool coated TiAlN coated TiAlN
Number of blades 2 2
[v.sub.c] [m/min] 50 80
f [mm/rev.] 0.05 0.19
Nr. of operation 3. 4.
Technology Chamfering Reaming
operation
Dimension [mm] 0.5 x 45[degrees] [??] 12H7 x 50
Material of the Sintered carbide Cermet
cutting tool coated TiN
Number of blades 1 6
[v.sub.c] [m/min] 100 Variables
f [mm/rev.] 0.1
Table 3. Experimental plan
Level of the factor
Code Labelling Unit -[alpha] -1 0
[x.sub.1] [v.sub.c] m/min 150 160 180
(cutting speed)
[x.sub.2] f mm/rev. 0.6 0.64 0.72
(feed rate)
[x.sub.3] [v.sub.f] mm/min 15 20 30
(reverse feed)
[x.sub.4] eccentricity [micro]m 2 4 8
Level of the factor
Code Labelling Unit +1 +[alpha]
[x.sub.1] [v.sub.c] m/min 200 210
(cutting speed)
[x.sub.2] f mm/rev. 0.8 0.84
(feed rate)
[x.sub.3] [v.sub.f] mm/min 40 45
(reverse feed)
[x.sub.4] eccentricity [micro]m 12 14
Table 4. Regression model suitability analysis
Parameter Value
RSquare 0.644137
RSquare Adj 0.555172
Root Mean Square Error 1.579146
Mean of Response 6.918407
Observations (or Sum Wgts) 26
Table 5. Regression model ANOVA
Sum of Mean
Source DF Squares Square F Ratio Prob > F
Model 5 90.27569 18.0551 7.2403 0.0005
Error 20 49.87404 2.4937
C. Total 25 140.14974
Table 6. Lack of Fit test
Sum of Mean
Source DF Squares Square F Ratio Prob > F Max RSq
Lack of Fit 9 20.649730 2.29441 0.8636 0.5840 0.7915
Pure Error 11 29.224315 2.65676
Total Error 20 49.874045
Table 7. Regression model parameters estimation
Prob > [absolute
Term Estimate Std Error t Ratio value of (t)]
Intercept 6.9184069 0.309696 22.34 < 0.0001
[x.sub.1] 0.3032367 0.349641 0.87 0.3961
[x.sub.2] -0.731483 0.349641 -2.09 0.0494
[x.sub.3] -0.343103 0.349641 -0.98 0.3382
[x.sub.2]. -1.767653 0.394787 -4.48 0.0002
[x.sub.1]
[x.sub.2] . 1.2522606 0.394787 3.17 0.0048
[x.sub.1] .
[x.sub.3]
Term Lower 95 % Upper 95 % VIF
Intercept 6.2723923 7.5644215 .
[x.sub.1] -0.426102 1.0325751 1
[x.sub.2] -1.460821 -0.002144 1
[x.sub.3] -1.072441 0.3862352 1
[x.sub.2]. -2.591163 -0.944143 1
[x.sub.1]
[x.sub.2] . 0.4287504 2.0757709 1
[x.sub.1] .
[x.sub.3]
Table 8. Influence of tool tip eccentricity on real diameter of
reamed hole
Measured diameter
Eccentricity [mm]
O.Nr. Clamping system [[micro]m] D up D down
1. Compensation tool holder 4 12,0168 12,0179
2. Compensation tool holder 12 12,0166 12,0178
3. Compensation tool holder 26 12,0169 12,0177
4. Hydraulic tool holder 26 12,0168 12,0179
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