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A. INTRODUCTION OF DISSERTATION
1. Dissertation title
Optimization on determination of dressing parameters, lubricant
conditions and exchanged grinding wheel diameter in internal cylindrical
grinding process
2. Rationale of the study
Nowadays, according to the great development of technologies,
machining processes have to satisfy more and more requirements of
mechanical products for quality as well as productivity. In reality, among
machining processes, grinding is commonly used to obtain the high quality
of surface finish. Especially, it predominates in machining annealed
products with high hardness, high strength. It accounts for about 20-25% of
the total expenditures for mechanical parts in industries. Because of these
reasons, improvement of grinding performance and reduction of machining
expenditure while remaining accuracy requirement have been interested in
researchers.
In comparison with other type of grinding, internal cylindrical grinding
process is implemented in difficult conditions and tight spaces. For that
reason, it is more difficult to study the process of internal grinding.
Therefore, the research of the internal grinding process is less interested by

scientists than studying external grinding or surface grinding.
In order to improve the internal grinding performance, many solutions
have been proposed such as using high standard grinding wheels (diamond
or CBN wheel), high speed grinding and optimizing grinding process
parameters (cutting, dressing and lubricant parameters). Among these
solutions, optimization of grinding process parameters has been considered
in many studies.
90CrSi is steel alloy with high mechanic strength and abrasion
resistance. It is commonly applied to make molds, low speed cutting tools
and machine parts required high durable and abrasion resistance. In medical
factories in the North of Vietnam, this type of steel is often used for making
tablet punches and dies.
Although, internal grinding process has been used in finished step for
making tablet dies, its quality and productivity are still low. Therefore, the


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results of this dissertation will provide suitable suggestions to improve the
efficiency of the internal grinding process when making these parts.
Based on previous studies, to increase the productivity and to reduce the
grinding cost, there are three proposed solutions including using optimum
lubricating-cooling condition, optimum dressing condition and using
optimum exchanged grinding wheel diameter.
3. Research objects
This study focuses on the internal grinding process for annealed 90CrSi
steel alloy.
4. Research aims and objectives
The aim of this study is to improve internal grinding process to reduce
grinding cost and surface roughness and increase productivity.
5. Research methodology
The proposed methodology is combined both theoretical and
experimental studies.
Theoretical study: internal grinding technologies and grinding cost
calculation are analyzed and synthesized.
Experimental study: the influence of lubricating-cooling parameters,
dressing parameters and exchanged grinding wheel diameter on the internal
grinding cost analyzed and optimized based in experiments.
6. Research contents
Overview of internal grinding technologies; Study on effect of
lubricating-cooling parameter, dressing parameter on surface roughness and
grinding productivity; Study on the calculation model of internal grinding
cost and the influences of grinding process on grinding cost; Determination
of optimal exchanged grinding wheel diameter.
7. New contributions
This study has analyzed the internal grinding cost and the influence of
grinding process parameters on the grinding cost.
Determining model to calculate the optimal exchanged grinding wheel
diameter (or optimum wheel lifetime) in internal grinding process and the
influence of grinding process parameters on the optimal exchanged wheel
diameter.


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The lubricating-cooling parameters and dressing parameters have been
analyzed and optimized based on grinding experiments of 90CrSi steel
alloy.
8. Dissertation structure
The dissertation includes the following parts: Introduction, 5 chapters,
conclusions and appendix.
Chapter 1: Overview of internal grinding process.
Chapter 2: The model of efficiency improvement of internal grinding
process and experimental system.
Chapter 3: Experimental study on influence of lubricating-cooling
parameter in internal grinding process
Chapter 4: Experimental study on influence of dressing parameter in
internal grinding process
Chapter5: Determination of optimal exchanged grinding wheel diameter.
9. Significances
Science significances
This dissertation has studied the influence of lubricating-cooling
parameters and dressing parameters on the surface roughness as well as the
grinding productivity when internal grinding 90CrSi steel alloy. The model
of grinding cost has been developed relating to the proposed formula of the
optimal exchanged grinding wheel diameter. This research has provided a
significant contribution in the reduction of grinding cost that is one of
interested research directions in internal grinding process.
Reality significances
This study has determined solutions to improve the internal grinding
efficiency to increase the grinding productivity and the reduction of the
grinding cost when grinding 90CrSi tool steel. The results of this study can
be applied for internal grinding tablet dies.


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B. DISSERATION OUTLINES
CHAPTER 1. OVERVIEW OF INTERNAL GRINDING PROCESSS
1.1. Internal grinding process: grinding schema, grinding shaft, position
and role of internal grinding in machining process.
1.2. Properties of internal grinding process.
- The properties of internal grinding process are grinding chord length l k,
grinding depth az, equivalent grinding wheel diameter Dtd, shaving removal
process of grinding grains, grinding productivity, grinding forces.
- Wear of grinding wheel.
- Grinding wheel life and method to determine it.
- Surface roughness.
- Topography of grinding wheel and method to measure Topography
1.3. Literature of internal grinding process.
This section focuses on researches relating to the influences of
lubricating-cooling, grinding and dressing parameter on the ground surface
in the internal grinding process. In addition, the models to determine
grinding cost such as Tarasow – Shaw, Field and Ebbrells – Rowe are
reviewed and analyzed.
1.4. Proposal solution to improve grinding efficiency

-

Determination of appropriate lubricating-cooling conditions;
Determination of optimal dressing parameters;
Determination of optimal grinding wheel life (optimal exchanged
grinding wheel diameter).

CHAPTER 2. MODEL TO IMPROVE THE EFFICIENCY OF
INTERNAL GRINDING PROCESS AND DEVELOPMENT OF
EXPERIMENTAL SYSTEM
2.1. Model to improve the efficiency of internal grinding process
Normally, researches focus on the technical efficiency of the grinding
process to improve the accuracy and the ground surface quality; reduce
force, heat, vibration or increase productivity. In order to solve both
directions, the dissertation develops a model to improve the efficiency of
the internal cylindrical grinding process. This model has been proposed


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including three parts to increase accuracy and machining surface quality and
reduce grinding cost in internal cylindrical grinding process.
Part 1: Input parameters.
Internal grinding process is complex under the influences of many input
parameters. These input parameters can be classified into five groups
including: grinding machines and cutting parameters; workpieces; grinding
wheels; dressing technologies and lubricating-cooling technologies. Among
these five input groups, some significant groups can be chosen to be
studied.

Figure 1. Model to improve the efficiency of internal grinding process
Part 2: Solutions to improve the efficiency of internal grinding process
Three solutions to improve the efficiency of internal grinding process
including finding optimal lubricating-cooling parameters to reduce surface
roughness and increase the grinding wheel life; finding optimal the dressing
parameters to increase the grinding wheel life and the grinding productivity;
finding the optimal grinding wheel life to reduce the grinding cost. These
models will be presents in next chapter respectively.
Part 3: The quality of the grinding process is increased and technical
requirements are ensured, productivity is increased and grinding cost is
decreased. All of the input lubricating-cooling parameters and dressing
parameters affect the surface roughness.


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Grinding cost per product
Ct,p (VNĐ)

Based on these arguments, it can provide a model to improve the
efficiency of the internal grinding process as shown in Figure 1.
Three solutions are proposed for studying to improve the efficiency of
the process when internal cylindrical grinding small holes. Among these
solutions, the application of the optimal grinding wheel life (exchanged
grinding wheel diameter) has not been considered in previous researches.
Figure 2 presents the relationship between the grinding wheel life (L),
grinding cost (Cgw,p) and cost of machine, labor and management (Cmt,p) in
internal grinding process for one product.

Cmt,p
Ct,pmin; Lop

Cgw,p
Ct,p

Grinding wheel life- L (hour)

Figure 2. The relationship between the grinding wheel life and grinding
cost
The longer the grinding wheel life, the lower the cost of grinding wheel
is. In contrast, the cost for machines, labors and management linearly
increases with the machining time. The total machining cost for a part
includes the expenditures of grinding wheel, machines, labors and
management ... In Figure 2, a certain optimal grinding wheel life always
exists.
2.2. Experimental system
Experimental system includes technical system and measurement
devices
2.3. Conclusion of chapter 2.
1. The input and output parameters have been analyzed and determined
as the following:
- Input parameters: Vđ, Vct, fa, fr, ae,tot, Cm,h, Cwa,h, dw, Rld tg, Srg, D0, Bgw,
wpd, Cgw, tw, tsđ, Ssđ, nsđ, NĐ, LL.
- Output: Ra, Ct,p and De,op


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2. This study has proposed a model to improve the efficiency of internal
grinding process including: determinations of the appropriate lubricatingcooling parameters, the optimal dressing parameters and the optimal
exchanged grinding wheel diameter. These solutions will be presented in
next chapters of this dissertation.
3. An experimental system has been developed to meet the requirements
of experimental research.
CHAPTER 3. EXPERIMENTAL STUDY ON INFLUENCE OF
LUBRICATING-COOLING PARAMETER IN INTERNAL
GRINDING PROCESS
3.1. Effect of cooling parameters on surface roughness
Cooling flood is the most commonly used in grinding hole. Therefore, in
this study, finding optimal coolant parameters is one of the directions to
improve the grinding efficiency.
3.1.1. Experiment and results/ Experimental results
a. Caltex Aquatex 3180 oil
Table 1. Experimental results for Caltex Aquatex 3180 oil
Code

Uncode

No.

Points

Flow
rate

Concentration

1
2
3
4
5
6
7
8
9
10
11
12
13

P6
P8
P3
P2
P9
P1
P9
P7
P9
P4
P5
P9
P9

-1
1
0
1
0
1,4
0
0
0
-1
-1,4
0
0

-1
-1
1,4
1
0
0
0
-1,4
0
1
0
0
0

Results and Discussions

Flow
rate
(l/m)
1
4
2,5
4
2,5
4,6
2,5
2,5
2,5
1
0,3
2,5
2,5

Concentration
(%)
2
2
5,6
5
3,5
3,5
3,5
1,3
3,5
5
3,5
3,5
3,5

Ra
(µm)
0,598
0,590
0,518
0,476
0,418
0,517
0,414
0,618
0,419
0,577
0,593
0,423
0,417


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The regression coefficients present the effect level of the flow rate, the
concentration parameters and their interaction on the objective function Ra.
They all have influence on the surface roughness, thus the regression
function is a quadratic function as below:
Y = 1,048 - 0,229x1 – 0,133x2 + 0,033x12 + 0,030x22 - 0,010x1x2 (1)
When this parameter increases, the roughness Ra decreases to minimal
value because friction is reduced. However, if the contribution is too high,
the coolant is concentrated and then amount of chips sticking on the
workpiece surface is increased. As a result, the surface roughness Ra is
increased. Similarly, the flow rate also affects on the roughness Ra. There is
an optimal flow rate to obtain a minimum roughness Ra. Increasing the flow
rate, more coolant is in the cutting area and then the roughness Ra is
reduced. However, the space of internal grinding is limited by the gring
wheel dimension, increasing the flow rate does not increase amount of the
coolant in cutting area. In addition, increasing the flow rate increases the
concentraion of the coolant in the cutting area and also increases the chips
on the workpiece surafce. That is an interaction effect between two
parameters on the roughness Ra.

Figure 3. Regression surface of Ra for Caltex Aquatex 3180 oil
b. Emulsion


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Table 2. Experimental results for Emulsion oil

No.

Points

1
2
3
4
5
6
7
8
9
10
11
12
13

P6
P8
P3
P2
P9
P1
P9
P7
P9
P4
P5
P9
P9

Code
Concentra
Flow
tion
rate
-1
1
0
1
0
1,4
0
0
0
-1
-1,4
0
0

-1
-1
1,4
1
0
0
0
-1,4
0
1
0
0
0

Uncode
Concentr
Flow rate
ation
(l/m)
(%)
1
3
4
3
2,5
6,6
4
6
2,5
4,5
4,6
4,5
2,5
4,5
2,5
2,4
2,5
4,5
1
6
0,38
4,5
2,5
4,5
2,5
4,5

Ra
(µm)
0,303
0,42
0,45
0,435
0,377
0,445
0,366
0,311
0,371
0,487
0,452
0,354
0,356

Results and Discussions
Using Minitab software, analyzing the experiment results, we obtained
the regression equation:
Y= 0,218 – 0,006x1+0,038x2 - 0,016x1x2 + 0,016x12 + 0,004x22
(2)

Figure 4. Regression surface of Ra for Emulsion oil


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In figure 4, when the flow rate is low, the concentration strongly affects
to the roughness value. Increasing the concentration, surface roughness
increase. When flow rate equal 4 l/min, the roughness value is almost
constant for all concentration value. In general, the more Emulsion oil will
increase the surface roughness. This is because Emulsion solution is high
density, makes it difficult to escape chips and clean the machining surface.
3.1.2. Optimization of the concentration and the flow rate
a. Caltex Aquatex 3180 oil
Using response surface method, the relation between the concentration
and the flow rate with the roughness Ra is shown. From the optimization
plot, there exists an optimal set of these parameters to obtain a minimum
roughness Ra. The solution of the optimal parameters are shown, the
minimal roughness Ra is 0.4102µm with the concentration of 3.907% and
the flow rate of 2.864 (l/min).
b. Emulsion oil
Similarly, we can determine the optimal cooling parameters when using
Emulsion oil solution. The flow rate value is 1,38 l/min and the
concentration value is 2,37%. The minimum of surface roughness Ramin =
0,3 µm
3.2. Conclusion of chapter 3.
This chapter focuses on experimental study on influence of 2 types (Caltex
Aquatex 3180 and Emulsion), lubricating-cooling parameter to surface
roughness in internal grinding process. This study results show that:
- When grinding and using Emulsion oil solution, surface roughness is
better than using Caltex Aquatex 3180 oil solution.
- The optimal Aquatex 3180, Emulsion oil solution lubricating-cooling
parameter with was determined.
+ With Aquatex 3180 oil solution: the flow rate is 2,86 l/min and the
concentration is 3,91%
+ With Emulsion solution: the flow rate is 1,38 l/min and the
concentration is 2,37%.


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CHAPTER 4. EXPERIMENTAL STUDY ON INFLUENCE OF
DRESSING PARAMETER IN INTERNAL GRINDING PROCESS
4.1. Experimental setup
Table 3. Dressing parameters and their values at different levels
Levels
TT
Factor
Symbol
1
2
3
4
5
6
Non-feeding
1
CK
0
1
2
3
4
5
dressing times
Coarse
2
dressing
ttho
0,02 0,025 0,03
depth (mm)
Coarse
3
ntho
1
2
3
dressing times
Fine dressing
4
ttinh
0,005 0,01 0,015
depth (mm)
Fine dressing
5
ntinh
1
2
3
times
Dressing feed
6
Ssd
1
1,2
1,4
rate (m/p)
Dressing has 3 steps: coarse dressing, fine dressing and non-feeding
dressing (Spark-out dressing). Dressing parameters included 6 factor:
Coarse dressing depth, Coarse dressing times, Fine dressing depth, Fine
dressing times and dressing feed rate.
Using Minitab, the experiment setup was design. The experiment with
the six dressing parameters including the dressing feed rate, the coarse
dressing depth, the coarse dressing times, the fine dressing depth, the fine
dressing times and the dressing number without depth of cut was conducted
using Taguchi method. Table 2 shows the dressing parameters and their
values at different levels. As it can be seen from the table, five three-level
dressing parameters and one six-level dressing parameter are established for
the experiment. The L18 (53x16) was used for the experiment work.


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Mean of Ra

4.2. Effect of dressing parameter to surface roughness (Ra) and
material remove rate (MRR) in internal grinding.
4.2.1. Experiment results and single-objective optimization.
a, Influence of dressing parameter to Ra
From the analysis of variance – ANOVA, it is clearly seen that the nonfeeding dressing times has the largest effect on surface roughness Ra, The
other parameters, which have the effect on Ra, sequence: coarse dressing
depth, coarse dressing times, fine dressing depth, fine dressing times and
dressing feed rate.
Table 4. The effect of dressing parameters on Ra at their levels
Level
CK
ttho
ntho
ttinh
ntinh
Ssd
1
0,4043
0,4929
0,4797 0,5193 0,5146 0,5023
2
0,4407
0,4808
0,5034 0,4836 0,5059 0,5144
3
0,4542
0,5396
0,5302 0,5104 0,4929 0,4967
4
0,5453
5
0,6193
6
0,5629
Delta
0,2150
0,0588
0,0505 0,0357 0,0217 0,0177
Rank
1
2
3
4
5
6

Figure 5. Effect of dressing parameters on Ra
Discussion:


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Mean of S/N ratio

If dressing has not the non-feeding dressing times, topography of
grinding will become rougher. The space for escaping, containing chip is
larger, so cutting heat, force and roughness decrease. The more non-feeding
dressing times reduce, the more ridiculous peaks will be reduced and thus
increasing Ra
Dressing depth increases, surface is rougher, grinding wheel time life
and MRR increase (suitable for rough grinding). Coarse dressing times
increase, thus Ra increase. The reason is that coarse dressing times increase,
number of undulating peaks in grinding increases and Ra increase.
Fine dressing depth is too small, leading to the undulating height on
surface grinding small, so that difficult to contain and escape chips, leading
to Ra increase. In other way, fine dressing depth increase, the undulating
height on surface grinding is higher but quickly flattened, so that grinding
wheel is worn out rapidly and Ra increase.
b. Optimum Surface roughness

Figure 6. Effect of dressing parameters on S/N
The optimal value of Ra is determined by the parameter level (circle) in
figure 6: CK = 0 time (A1); ttho = 0,025 mm (B2); ntho = 1 time (C1); ttinh =
0,01mm (D2); ntinh = 3 time (E3); Ssd = 1,4 m/min (F3).
Optimum value of Ra
Ratoiuu  A1  B2  C1  D2  E3  F3  5.Tgg


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Substituting all of the parameters into equation
Ratoiuu  0.404  0.481  0.48  0.484  0.493  5x0.504  0.318m

A confidence interval (CI) can be computed as:
 1
1
CI   F 1, f e  , Ve , 
   0,14
N
R
 e


Where, 𝐹∝ (1, 𝑓𝑒 ) = 8,5262 is a coefficient for the confidence level
%=90%, fe =2 is the degree of freedom of error, Ve = 0,003822 is the
mean of error, R =3 is the number of trials in each experiment
𝑁𝑒 =

𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑡𝑒𝑠𝑡 𝑟𝑢𝑛𝑠
54
=
= 3,375
1 + 𝑠𝑢𝑚 𝑜𝑓 𝑑𝑒𝑔𝑟𝑒𝑒𝑠 𝑜𝑓 𝑓𝑟𝑒𝑒𝑑𝑜𝑚 𝑜𝑓 𝑡ℎ𝑒 𝑓𝑎𝑐𝑡𝑜𝑟 𝑖𝑛 𝐸𝑞 1 + 15

Based on  = 90% the predicted optimum material removal rate with the
optimum level of dressing parameters including nCK1/ttho2/ntho1/ttint2/ntinh3/S3:
(0,318 − 0,14) ≤ ̅̅̅̅
𝑅𝑎𝑜𝑝 ≤ (0,318 + 0,14) or 0,178 ≤ Raop ≤0,458 µm
c. Influence of dressing parameter to MRR.
Material removal rate MRR (mm3/s) is determined by the volume of
material removal per unit time. The volume of material removal during a
grinding process is determined by testing the hole diameter before and after
grinding. Grinding wheel life is determined by worker experience, grinding
force Py.
Table 5. The effect of dressing parameters on MRR
Level
CK
ttho
ntho
ttinh
ntinh
Ssd
1
2,109 2,446 2,450 2,577 2,253
2,355
2
2,033 2,463 2,384 2,314 2,382
2,426
3
2,475 2,318 2,393 2,336 2,591
2,445
4
2,462
5
2,438
6
2,937
Delta
0,905 0,146 0,066 0,264 0,338
0,090
Rank
1
4
6
3
2
5
From the analysis of variance – ANOVA, it is clearly seen that the
effect on MRR, sequence: non-feeding dressing times, fine dressing times,


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Mean of MRR

fine dressing depth, coarse dressing depth, dressing feed rate and coarse
dressing times.
Non-feeding dressing times has the largest effect on the material
removal rate. When number of non-feeding dressing times increase, MRR
will increase (op
The number of non-feeding dressing greatly affects the grinding
productivity. The higher the values of it, the higher productivity (as opposed
to affecting Ra). When increasing the number of non-feeding dressing, the
finer the surface of the grinding, the more blade density and the number of
slots for keeping chips are high.

Figure 7. Effect of dressing parameters on MRR
The increase of the dressing depth of cut leads to the reduction of the
productivity. The dressing depth of cut from 0.02mm to 0.025mm hardly
changes the MRR and when the roughness equals 0.03mm, the MRR
decreases. When the dressing depth of cut increases from 0.005mm to
0.01mm, the MRR decreases and when the ttinh increased to 0.015mm, the
MRR did not increase much. This is because with the increase of the
dressing depth of cut, MRR reduces.
The number of rough dressing has almost no effect on MRR. The
number of fine dressing is the second most powerful factor on MRR after
the number of superfine dressing. MRR is proportional to the number of
fine dressing.


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The dressing feed does not affect much to the MRR (similar to the
affecting to Ra).
d. Optimization of MRR
The value MRR max is determined by the following equation at levels:
CK (A6); ttho (B2); ntho (C1); ttinh (D1); ntinh (E3); Ssđ (F3).
MRRtoiuu  A5  B2  C1  D1  E3  F3  5.Tgg

And we have: MRRtoiuu  3, 42(mm3 / s)
The CI confidence interval is calculated as follows:
 1 1
CI   F 1, f e  ,Ve , 
   0, 415
 Ne R 

Mean of S/N ratio

Where, 𝐹∝ (1, 𝑓𝑒 ) = 8,5262 is a coefficient with significance level
%=90%, fe =2 is the degree of freedom of error, Ve = 0,032125 is the
average error, neff is the number of effective iterations, R = 3 is the number
of iterations of an experiment.

Figure 8. Effect of factors on S/N of MRR
𝑁𝑒 =

𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑒𝑥𝑝𝑒𝑟𝑖𝑚𝑒𝑛𝑡𝑠
54
=
1 + 𝑇ℎ𝑒 𝑡𝑜𝑡𝑎𝑙 𝑑𝑒𝑔𝑟𝑒𝑒𝑠 𝑜𝑓 𝑐𝑜𝑚𝑝𝑢𝑡𝑎𝑡𝑖𝑜𝑛𝑎𝑙 𝑓𝑎𝑐𝑡𝑜𝑟𝑠 𝑖𝑛 𝑜𝑝𝑡𝑖𝑚𝑎𝑙 𝑓𝑜𝑟𝑚𝑢𝑙𝑎 1 + 15
= 3,375

Accordingly, with significance level  = 90% the surface roughness is
predicted
with
the
optimum
level
of
input
parameters
nCK6/ttho2/ntho1/ttint1/ntinh3/S3 such as:


17
2.973  MRRop  3.803(mm3 / s)

4.3. Multi-objective optimization
In this study, a combination of Taguchi and GRA methods was used to
optimize the negotiation of two outputs of the dressing mode when internal
grinding: MRR and Ra.
The greatest value of gray relation of each factor is the optimal level of
that factor. Therefore, according to Figure 9, the optimal parameters of the
dressing process when internal grinding meet both surface roughness
minimum and MRR maximum are:
ttho1/ntho1/CK6/ntinh3/ttinh1/Ssđ3 corresponding to ttho=0,02mm, ntho = 1
times, CK = 5 times, ntinh = 3 times, ttinh = 0,005 mm, Ssđ = 1,4 m/ph.
Whereby:
(𝑅𝑎) 𝑇𝑜𝑖𝑢𝑢 = 0,4929 + 0,4797 + 0,563 + 0,5193 + 0,4929 + 0,4966 − 5
∗ 0,5045 = 0,522 µ𝑚
(𝑀𝑅𝑅) 𝑇𝑜𝑖𝑢𝑢 = 2,446 + 2,45 + 2,937 + 2,577 + 2,591 + 2,445 − 5
∗ 2,4089 = 3,402 𝑚𝑚3 /𝑠

Figure 9. Main effect plot for means
4.4. Conclusions of chapter 4
1. The process of dressing should follow rough, fine and super fine
dressing steps to help stabilize the topography of the wheel. The number of
times the super fine dressing has the greatest effect on the surface roughness
and the grinding performance. The super fine dressing can reduce the
surface roughness but it can help to increase the grinding productivity


18
significantly. The greater the depth of rough dressing and fine dressing can
increase the surface roughness and reduce the MRR. Therefore, it is
advisable to choose a suitable depth of dressing. The larger of the number of
rough dressing also increase the surface roughness and reduce the MRR.
Also, the more fine dressing times will help reduce the surface roughness
and increase MRR.
2. The results of the study help to choose the optimum dressing mode
when internal grinding 90CrSi tool:
+) For minimum surface roughness (fine grinding) the optimum dressing
parameters are: (CK = 0; ttho = 0,025mm; ntho = 1; ttinh = 0,01mm; ntinh = 3;
Ssđ = 1,4m/p) Ramin = 0,318µm
+) For maximum grinding productivities (rough grinding) the optimum
dressing parameters are (CK = 5; ttho = 0,025mm; ntho = 1; ttinh = 0,005mm;
ntinh = 3; Ssđ = 1,4m/p) MRRmax = 3,42 mm3/s)
+) For multi-objective optimization CK = 5, ttho =0,02mm; ntho = 1, ttinh =
0,005mm, ntinh = 3, Ssđ = 1,4m/p and MRR = 3,402mm3/s, Ra = 0,522µm.
CHƯƠNG 5. OPTIMIZATION OF EXCHANGED GRINDING
WHEEL DIAMETER
This chapter will investigate the determination of the optimum
exchanged grinding wheel diameter and the effect of the parameters on the
optimum exchanged diameter based on the analysis of grinding costs. In
addition, the effectiveness of applying the optimum diameter in internal
grinding is also indicated.
5.1. Cost analysis
Based on previous researches on cost models for machining process, a
new cost model that calculates the cost of the internal grinding process has
been proposed. As follows:

Ct , p  (Cwa ,h  Cm ,h ).tt  Cgw, p  Cmt ,h .tt  C gw, p
Where,
Cmt,h machine cost (VNĐ/h)
Cwa,h administration cost and labor cost (VNĐ/h)
Cgw,p grinding wheel cost (VNĐ)
tt is total time for grinding one part (h)


19
Ct , p 

2(w pd  aed ).tcw    2(w pd  aed ).tc
Cm,h  Cwa ,h 
 t

. t L  t s  t c  1  d 
Cgw 
  
60
t
(
D

D
).
t
(
D

D
).
t
w
0
e
w
0
e
w

 



5.2. Effect of parameters on the cost of the internal grinding process
As mentioned in section 5.1, the grinding cost when internal grinding is
affected by many parameters. These parameters include 18 grinding
parameters such as the original diameter of the stone, the width of the
grinding wheel, the hole diameter, the number of vertical feed speed, the
diameter of the grinding wheel, etc., and the cost components such as the
machine cost, the labor cost, the grinding wheel cost, etc.
Factors that significantly affect the cost of grinding include Rld, tw, ae,tot,
Cgw, Cm,h, D0,  and . In addition, factors D0, tg, td, wpd, aed, Cwa,h, Srg, Bgw
are the small impacting factors on the cost. Especially, factors Srg, Bgw, aed,
wpd, Cwa,h are negligible impact on internal grinding cost.
Among the influencing parameters, the ratio between the length and hole
diameter Rld (J) is the most powerful factor affecting internal grinding cost.
This is because the deeper the hole, the harder it is to grind and requires
more complex grinding technology.
The cost of machine Cm,h, the labor cost and the hourly management of
Cwa,h and the cost of grinding wheel Cgw a positive effect on the processing
cost. This means that when these values increase, the grinding cost
increases.
The increase in the dressing depth will lead to the increase of the cost
but its impact was not significant. Also, the dressing time td is a factor that
does not significantly affect the cost. If td increases, the cost increases. This
is because the longer of the dressing time, the more time it takes to sharpen
and lead to increased grinding costs. Therefore, to reduce the cost of
grinding, it is necessary to study the dressing process such as automating
the dressing process, reducing the time for replacing dressing tools ...
Besides, the total depth of grinding cut ae,tot is the most influential factor on
the grinding cost (ranked 3rd in the level of influence). The larger the
amount of the depth of cut, the more the time of grinding will increase and
lead to an increase in the cost of grinding. Therefore, the optimum depth of


20
cut should be selected appropriately, in accordance with machining
requirements in order to reduce the cost.
The most powerful impact on the grinding cost is the ratio of the hole
length to hole diameter Rld and the part diameter. When this ratio is larger
the grinding cost will increase. Meanwhile, the processing conditions will
be harsher and the horizontal feed speed cannot be large. Also, the amount
of removal material is also large, thus increasing the grinding cost. In
addition, the greater the surface roughness grade Srg will increase the
grinding cost. So to reduce grinding costs should not choose the large Rld (if
possible).  is a factor closely related to the original part diameter d w and
the initial grinding diameter D0. Increasing the ratio  will increase the
grinding cost.
As analyzed above, the increase in grinding wheel cost will increase the
grinding cost. However, the higher the wheel lifetime will reduce the cost.
Also, the impact of wheel lifetime is greater than the impact of wheel cost.
In addition, the amount of wheel wear wpd and the width of wheel B gw do
not affect the grinding cost much. Therefore, if we use high quality grinding
wheel (expensive, durable) we can reduce the grinding cost. In addition,
optimizing grinding parameters to increase the wheel lifetime also helps to
reduce the grinding cost.
The initial wheel diameter D0 and the hole diameter are two parameters
depending on the coefficient . Therefore, increasing D0 can increase the
average cutting speed and reduce the machining time. However, in this case,
the processing conditions are also changed. Therefore, the amount of
removal material increases and increases the cost of grinding. Besides, the
exchanged wheel diameter De also affects the grinding cost. When delta (De
/ D0) decreases (or De decreases), it will reduce the grinding cost.
5.3. Optimal exchanged wheel diameter
5.3.1. Determining optimal exchanged wheel diameter
Figure 10 describes the relationship between the cost of grinding a part
(VND / h) and the exchanged wheel diameter (mm). This relationship is
built based on the calculation according to the formula in Section 4.1 with
the following data: D0=20 (mm); Bgw=25 (mm); aed=0,12 (mm);
Cm,h=70.000 (VNĐ/h); Cwa,h=46.000 (VNĐ/h); Cgw=70.000 (VNĐ); tw=20


21

Grinding cost per product Ct,p (VNĐ)

(min); wpd=0,02 (mm); tg=7; Rld=2, td=0,3 (min), tcw=2,4 (phút), tL=0,54
(min), ts=0,3(min), Srg = 7, dw=25 (mm), ae,tot=0,1 (mm). From this figure, it
can be seen that the grinding cost depends heavily on the exchanged wheel
diameter (or the wheel lifetime). In addition, there exists an optimal
exchanged wheel diameter at which the grinding cost is minimum (Cmin =
5,927 VND; De,op = 17,5mm). The value of this optimal exchanged wheel
diameter is much larger than that of traditional exchanged wheel diameter
(in this case, about 14 mm).

8100
7600
7100

C = 6.528VNĐ
Demin = 14

6600

Cmin = 5.927 VNĐ
De,op = 17,5

6100
5600

13

14

15

16

17

18

19

20

Exchanged grinding wheel diameter - De (mm)

Figue10. Exchanged wheel diameter versus grinding cost
As mentioned above, because the exchanged wheel diameter greatly
affects the cost of grinding, finding the value of the optimal exchanged
wheel diameter will help to reduce grinding cost significantly. When
comparing the cost of grinding when changing the wheel at the optimum
exchanged diameter De, op = 17.5mm with the cost of replacing the wheel
at the traditional exchanged diameter, min = 14mm, it is found that the cost
reduced from 6,528 VND/ part to only 5,927 VND / part (down 9.02%).
The average total grinding time decreased from 192 (seconds) to 164
(seconds) (down 14.7%).
5.3.2. Effect of process parameters on the exchanged wheel diameter
D0 greatest impact on the exchanged wheel diameter De,op, next are
D0*tw, D0*Cgw, Cgw, tw, D0*Cmh, Cm,h, Cwa,h, tw*Cgw, D0*Cwah, D0*aed,


22
Cmh*Cwah, Cmh*Cgw, aed and Bgw*aed. The ratio Rld, the wheel wear wpd, the
accuracy grade tg does not affect De,op.
5.3.3. Modeling optimal exchanged wheel diameter
The relation equation between De,op and the main influencing parameters
can be written 5 with the correlation coefficient r2 = 99,63%.
De,op = -2.614 + 0.6620 D0 + 0.0408 Bgw + 7.45 aed - 0.0304 tw
+ 0.000003 Cm,h + 0.000010 Cwa,h - 0.000011 Cgw - 0.5421 D0*aed
+ 0.008034 D0*tw + 0.000001 D0*Cwa,h - 0.000001 D0*Cgw
- 0.416 Bgw*aed
5.4. Conclusions of chapter 5
1. A model for calculating the grinding cost when internal grinding with
a number of parameters has been built. From this model the effect of
grinding process parameters and several cost components on the grinding
cost was investigated. Thereby some conclusions were given:
- The ratio between the length and diameter of the hole has the strongest
impact on grinding cost;
- The cost of machine, the labor cost and the grinding wheel cost have a
significant effect on the grinding cost. The cost of grinding will increase
when these costs increase;
- Some solutions to reduce the cost of grinding have been proposed,
such as reducing the cost of machines, the cost of grinding wheel, the labor
costs (workers, management ...); Using abrasive wheel with high durability
and studying methods to improve the wheel lifetime and determine the
appropriate amount of dressing depth of cut; Finding methods to reduce the
dressing time and the time for changing dressing tools...
2. The exchanged wheel diameter greatly affects the cost of grinding.
Also, there exists an optimal value of the exchanged wheel diameter at
which the grinding cost is minimal. In addition, a formula to determine the
optimal exchanged grinding wheel diameter De, op has been proposed.
3. The influence of these factors on the optimum exchanged wheel
diameter is as follows: The initial diameter of the grinding wheel D0 has the
strongest influence on the exchanged grinding wheel diameter De,op, next is
the grinding wheel cost Cgw, the wheel lifetime tw, the machine cost Cm,h,
the labor cost Cwa,h. Also, the dressing depth of cut aeđ. The ratio Rld, the
wheel wear wpd, the accuracy grade tg do not affect De,op. The quadratic


23
factors influence De,op are D0*tw, D0*Cgw, D0*Cmh, tw*Cgw, D0*Cwah, D0*aed,
Cmh*Cwah, Cmh*Cgw and the final is Bgw*aed.
- The economic efficiency of applying the optimum exchanged wheel
diameter helps to reduce the cost of grinding per part by 9.02%, the total
grinding time decreases by 14.7%.
CONCLUSIONS AND RECOMMENDATION
Conclusions
The objective of this thesis is to improve the efficiency of internal
grinding process. In order to do that, it is necessary to solve the following
problems: Determining a reasonable cooling lubrication mode, determining
a reasonable dressing parameters and determining the optimal exchanged
wheel diameter. The main results and new contributions of the thesis can be
summarized as follows:
1. Proposing models to improve efficiency when internal grinding. Since
then propose solutions to improve the efficiency when grinding.
2. Experimental study of the effects of the flow rate, the concentration of
coolant solutions of the two types of coolants including Aquatex 3180 and
Emulsion on the surface roughness and proposed the optimal coolant
method for the two types of solutions when internal grinding of 90CrSi tool
steel.
3. Researched the effect of the dressing parameters on the surface
roughness and the grinding performance. The proposed dressing process is
divided into 03 steps: rough dressing, fine dressing and super fine dressing.
In particular, the number of times the super fine dressing is most strongly
influenced by the surface roughness and the grinding performance. The
optimal dressing parameters when grinding 90CrSi tool steel has helped
improve the surface quality and increase the productivity significantly.
4. Develop a model to calculate the cost of internal grinding and
investigate the impact of factors on the grinding cost. In this model, the
impact of 18 factors of grinding cost is included. These factors include
component costs such as grinding costs, human costs (including labor,
management, etc.), grinding wheel costs, etc. and grinding process
parameters such as the initial wheel diameter, the wheel width, the wheel


24
wear, the total dressing depth of cut, the dressing time have taken into
investigation.
5. Building a method of determining the optimal exchanged wheel
diameter when internal grinding to achieve the lowest grinding cost based
on building and solving a cost optimization problem. By applying the
formula of optimal exchanged grinding wheel diameter, the grinding cost
can be reduced by 9.02%, the total grinding time is reduced by 14.7%. This
method is applicable in cases where the grinder is unable to change the
spindle rotation speed.
Recommendation
Although this research has found a number of solutions to improve the
efficiency of internal grinding process, there are still issues that need further
investment in research. Specifically include the following research
directions:
1) Research on the method to supply of the coolant into deep areas of
grinding.
2)

Cutting conditions when grinding small and deep holes with the
diameter less than 10 mm are very fierce. Therefore, it is needed
further researches.

3)

Investigation of the effects of coolant parameters and dressing
parameters on the mechanical and physical properties of the workpiece
surface.


25
LIST OF PUBLISHED WORKS RELATED TO THE THESIS
* Internal journal papers
1. Banh Tien Long, Vu Ngoc Pi, Le Xuan Hung, Ta Viet Cuong, A study on the
effects of coolant regimes to surfaceroughness in in ternalgrinding of steel 9XC,
VietNam Mechanical Engineering Journal, Vol 5, 2016, pp 71 – 76 (In Vietnamese)
2. Banh Tien Long, Vu Ngoc Pi, Le Xuan Hung, Luu Anh Tung, Buiding
cutting regime formulas for internal grinding, TNU Journal of Science and
Technology, Vol 9, 2016, page 15 – 18 (In Vietnamese).
* Internatinonal journal papers
3. Vu Ngoc Pi, Le Xuan Hung, Luu Anh Tung and Banh Tien Long, “Cost
Optimization of Internal Grinding”, Journal of Materials Science and Engineering B
6 (11-12) (2016) page 291 – 296.
4. Le Xuan Hung, Tran Thi Hong, Le Hong Ky, Luu Anh Tung, Nguyen Thi
Thanh Nga, Vu Ngoc Pi, “Optimum dressing parameters for maximum material
removal rate when internal cylindrical grinding using Taguchi method”,
International Journal of Mechanical Engineering and Technology (IJMET), Volume
9, Issue 12, December 2018, pp. 123–129. Scopus
5. Le Xuan Hung, Vu Ngoc Pi, Tran Thi Hong, Le Hong Ky, Vu Thi Lien, Luu
Anh Tung, Banh Tien Long, “Multi-objective Optimization of Dressing Parameters
of Internal Cylindrical Grinding for 90CrSi Alloy Steel Using Taguchi Method and
Grey Relational Analysis”, 9th International Conference on Materials Processing
and Characterization, 8th – 10th March 2019, Materials Today: Proceedings,
Available online at www.sciencedirect.com. Scopus (Accepted)
6. Le Xuan Hung, Tran Thi Hong, Le Hong Ky, Nguyen Quoc Tuan, Luu Anh
Tung, Banh Tien Long, Vu Ngoc Pi, A study on calculation of optimum exchanged
grinding wheel diameter when internal grinding, 9th International Conference on
Materials Processing and Characterization, 8th – 10th March 2019, Materials
Today: Proceedings, Available online at www.sciencedirect.com. Scopus
(Accepted)
7. Le Xuan Hung, Vu Thi Lien, Luu Anh Tung, Vu Ngoc Pi, Le Hong Ky, Tran
Thi Hong, Hoang Tien Dung, Banh Tien Long, “A study on cost optimization of
internal cylindrical grinding”, International Journal of Mechanical Engineering and
Technology (IJMET), Volume 10, Issue 1, January 2019, pp. 414 – 423. Scopus
8. Thi-Hong Tran, Xuan-Hung Le, Quoc-Tuan Nguyen, Hong-Ky Le, TienDung Hoang, Anh-Tung Luu, Tien-Long Banh and Ngoc-Pi Vu, “Optimization of
Replaced Grinding Wheel Diameter for Minimum Grinding Cost in Internal
Grinding”, Applied Sciences, 9(7), March, 2019, pp. 1363. SCIE
9. Le Xuan Hung, Vu Thi Lien, Vu Ngoc Pi, Banh Tien Long, “A Study on
Coolant Parameters in Internal Grinding of 90CrSi Steel”, Materials Science
Forum, Vol. 950, pp 24-31, Apirl, 2019 Trans Tech Publications, Switzerland.
Scopus


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