The research paper published by IJSER journal is about Surface Roughness Optimization Techniques of CNC Milling: A Review 1

ISSN 2229-5518

Surface Roughness Optimization Techniques of CNC Milling: A Review

Mandeep Chahal 1, Vikram Singh 2 , Rohit Garg3 , Sudhir Kumar4

1 Asstt. Professor , Deptt. Of Mechanical Engineering,

HCTM, Kaithal (Haryana), India Email: mandeepchahal02@gmail.com

2Associate Professor , Deptt. Of Mechanical Engineering, YMCAUST, Faridabad (Haryana), India Email: singhvikram77@gmail.com

3Professor, Deptt. Of Mechanical Engineering, IIET, Jind (Haryana), Email: rohit_garg123@yahoo.com

4 Professor , Deptt. Of Mechanical Engineering,

NIET, Greater Noida(U.P), India Email: s_k_tomar02@yahoo.com

Keywords: CNC Milling, Literature, Surface Roughness:

Abstract: Surface Roughness is mostly used as an index to determine the surface finish for continuous improvement of quality. A large number of publications by various authors reflect the interest in this technique. Reviews of literature on surface roughness optimization have been done in the past by a few authors. However, considering the contributions in the recent times, a more comprehensive review is attempted here. In this paper, the authors have reviewed the literature in a way that would help researchers, academicians and practitioners to take a closer look at the growth, development and applicability of this technique. The authors have examined various papers and have proposed a different scheme of classification. In addition, certain gaps that would provide hints for further research in this field have been identified.

INTRODUCTION: With the more precise demands of modern engineering products, the control of surface texture together has become more important. This review studies the various optimization methodologies, which is applied to optimize surface roughness in end milling operations. Conventional machining processes require a

lot of time and effort. The accuracy achieved
by such processes is not up to the level. With the invention of CNC machines, it becomes easy to do the various machining processes easily and accurately. Out of various machining processes, milling process has the advantage of multi-point cutting tool with high dimensional accuracy. So, it is important to study the various
parameters that affect the quality surface

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The research paper published by IJSER journal is about Surface Roughness Optimization Techniques of CNC Milling: A Review 2

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roughness to get the desired accuracy. Further, it is important to study which parameter affects the surface roughness significantly and the various optimization techniques. This can be done after a detailed literature review. Surface finish is important factor in evaluating the quality of products. Decision makers are constantly on the lookout for techniques to enable quality improvement. Surface Roughness Optimization is one such technique that has become popular in the recent times. The term surface finish is well known but the concept is understood more in qualitative terms than in quantitative terms. This is evident from the fact that many industries continue to specify finish as rough, good, smooth, glossy, mirror etc. None of these terms are sufficiently accurate and besides, they tend to convey different meanings to different people. It is in the common interest to adopt a quantitative method of evaluation with appropriate inspection techniques which will eliminate the variable subjective factor.

This paper, besides providing a review of literature on surface roughness optimization, covers the following

objectives:

(1) Describing the publications in an orderly manner to enable easy and quick search;
(2) Classification of various techniques that can be used for optimization of surface roughness;
(3) Outcome of publications; and
(4) Identifying gaps and providing hints for further research.
This paper first provides a comparison among the earlier reviews on surface roughness and highlights the outcome in each case. All new techniques have been discussed.
Six papers have been studied in detail to conclude:
 The various optimization techniques that can be used to get an optimal value of surface finish.
 Various parameters that affects the surface roughness.
 Which parameter affects the surface roughness significantly?
 Various surface roughness measuring instruments.
 Different attributes that can affect the quality of a product.
 Gaps in the existing literature.

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The research paper published by IJSER journal is about Surface Roughness Optimization Techniques of CNC Milling: A Review 3

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Detail of papers which have been reviewed in the present paper are:

(1) “Application of response surface methodology in the optimization of cutting conditions for surface roughness”, H.Oktem, T.Erzurumlu and H.Kurtaran, 2005, Journal of Materials Processing Technology 170(2005)11-16. (2)“Milling surface roughness prediction using evolutionary programming methods”, Oguz Colak, Cahit Kurbanoglu and M.Cengiz Kayacan,
2007, Journal of Materials & Design
28(2007)657-666.
(3)“Surface Roughness optimization in an end milling operation using Taguchi design method, Julie Z.Zhang, Joseph C.Chen and E.Daniel Kirby, 2007, Journal of Materials Processing Technology184(2007)233-239.
(4) “The effects of cutter path strategies on surface roughness of pocket milling of 1.2738 steel based on Taguchi method”, Cevdet Gologlu and Nazim Sakarya, 2008, Journal of Materials Processing Technology 206(2008)7-16. (5) “Optimization of CNC end milling process parameters using PCA based Taguchi method”, Sanjit Moshat et al,
2010, Internatonal Journal of
Engineering, Science & Technology
(2010)92-102.
(6) “Surface Roughness Prediction for CNC milling process using Artificial Neural Network”, M.F.F.Ab.Rashid and M.R.Abdul Lani, 2010, Proceedings of World Congress in Engineering.
A complete detail of each paper is required for describing all the aspects so that a new researcher can easily locate them, download them so that one can enhance his skills. This can be achieved by describing fully the paper. The papers are arranged in ascending order of their year of publication. These selected papers are studied in detail so that every aspect starting from the work piece, selection of machine, parameters to be taken for optimization, instrument to be used for measurement of surface roughness so that surface roughness at various locations of the work piece can be determined. Then, the various optimization technique that can be used for optimization by describing both single response optimization technique and multi optimization techniques so that value of various parameters like cutting speed, depth of cut and feed rate can be determined for optimization of surface roughness. For surface roughness smaller the better can be
used because it will yield greater surface

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The research paper published by IJSER journal is about Surface Roughness Optimization Techniques of CNC Milling: A Review 4

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finish. It is in the common interest to adopt a quantitative method of evaluation with appropriate inspection techniques which will eliminate the variable subjective factor. When different surfaces are compared, it is
possible to distinguish them in terms of
reflectivity (dull or shiny appearances), smoothness, the presence of chatter marks, or the visual scratch pattern. Table 1 shows the title , year of publication and the name of concerned journal.

Table No. 1 title of papers along with year & journal in which published

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The research paper published by IJSER journal is about Surface Roughness Optimization Techniques of CNC Milling: A Review 5

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These selected papers are then studied in detail so that every aspect of the work done by the researcher can be framed in a better
way. Outcomes of the reviews are shown in
Table 2. Further, a comparison among the earlier attempts to review literature is made using certain attributes.

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The research paper published by IJSER journal is about Surface Roughness Optimization Techniques of CNC Milling: A Review 6

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Table No. 2 showing Outcomes of the different reviews

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The research paper published by IJSER journal is about Surface Roughness Optimization Techniques of CNC Milling: A Review 7

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Surface roughness refers to deviation from the normal surface. Order of deviation is defined in international standards. First- and second-order deviations refer to forms, i.e. flatness, circularity, etc. and to waviness, respectively, and are due to machine tool errors, deformation of the work piece, erroneous setups and clamping, vibration and work piece material in homogeneity.
Third and fourth-order deviations refer to
periodic grooves and to cracks which are connected to the shape and condition of the cutting edges, chip formation and process kinematics. Fifth- and sixth-order deviations refer to work piece material structure, which is connected to physical–chemical mechanisms (slip, diffusion, oxidation, residual stress, etc.). Different order deviations are superimposed and form the
surface roughness profile, as in Fig. 2.

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The research paper published by IJSER journal is about Surface Roughness Optimization Techniques of CNC Milling: A Review 8

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Fig No. 2 Different order deviations

Selection of process parameters is based on literature review and researchers take these parameters with the help of cause and effect diagram. Surface finish depends on a number of factors shown by cause and effect

diagram as shown in fig 3.Out of these
parameters, machining parameters need to be studied in a detailed manner so that the surface roughness of a surface can be worked out and possibly be minimized from the engineering point of view.

CUTTING TOOL PROPERTIES

Tool wear

MACHINE PARAMETERS

Depth of cut

Nose radius

Tool shape

Tool material

Cutting speed

Feed rate

SURFACE FINISH

Chip formation

Vibration

Hardness

Friction in cutting zone

Cutting force

Shape

Material

CUTTING PHENOMENA

WORK PIECE PROPERTIES

Fig No. 3 Cause & Effect Diagram

Classification of affecting factors:

Table No. 3 Classification of affecting factors

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The research paper published by IJSER journal is about Surface Roughness Optimization Techniques of CNC Milling: A Review 9

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Now, we discuss how surface roughness measurement depends on a number of factors and how it can be measured.
It depends on:
 Instrument to be used for measurement.
 Techniques that can be used for measurement.
 Parameters that have a significant effect on surface roughness.
 Noise factors consideration.

Various instruments that can be used for measurement of surface roughness are:

 Image Processing.
 Microscope.
 Stylus type of instrument.
 Profile tracing instrument.
Image processing instrument shown in figure 4 can be used to detect surface roughness of a surface.

Fig No. 4 Image processing apparatus

Stylus instruments:

The Surftest SJ-201P (Mitutoyo) is a shop–
floor type surface-roughness measuring instrument, which traces the surface of various machined parts and calculates the surface roughness based on roughness
standards, and displays the results. The work piece is attached to the detector unit of the SJ-201P will trace the minute irregularities of the work piece surface. The vertical stylus displacement during the
tracing is processed and value is digitally

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The research paper published by IJSER journal is about Surface Roughness Optimization Techniques of CNC Milling: A Review 10

ISSN 2229-5518

displayed on the liquid crystal display of the
SJ-201P.The apparatus is shown in figure 5.

Fig No. 5 Mitutoyo Surftest SJ-201P Instrument

Mathematical techniques can also be used like:

Some of the popular parameters of surface finish specification are described as follows:

1 Roughness average (Ra)

This parameter is also known as the arithmetic mean roughness value, AA (arithmetic average) or CLA (center line average). Ra is universally recognized and the most used international parameter of roughness. Therefore,
Where,
Ra = the arithmetic average deviation from the mean line
L = the sampling length
y = the ordinate of the profile curve
It is the arithmetic mean of the departure of the roughness profile from the mean line.

2 Root-mean-square (RMS) roughnesses

(Rq)

This is the root-mean-square parameter corresponding to Ra:

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The research paper published by IJSER journal is about Surface Roughness Optimization Techniques of CNC Milling: A Review 11

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Fig No. 6 Variation of Surface Roughness

3 Maximum peak-to-valley roughness heights (Rmax)

This is the distance between two lines parallel to the mean line that contacts the extreme upper and lower points on the profile within the roughness sampling length. Since Ra and Rq are the most widely used surface parameters in industry, Ra was selected to express the surface roughness in this study.
The next step is to determine the various optimization techniques to calculate surface
roughness:

A number of optimization techniques can be used:

 Taguchi method
 PCA(Principle Component Analysis)
based Taguchi method
 RSM (Response Surface
Methodology)
 Artificial Neural Networks
 Average Roughness Technique
 ANOVAs Approach
These techniques can be explained in detail with the help of table 4.

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The research paper published by IJSER journal is about Surface Roughness Optimization Techniques of CNC Milling: A Review 12

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S.NO.

1.

TECHNIQUE NAME PCA-based Taguchi method

DETAIL

Taguchi’s Orthogonal Array (OA) provides a set of well-balanced experiments (with less number of experimental runs), and Taguchi’s signal-to-noise ratios (S/N), which are logarithmic functions of desired output. Principal Component Analysis (PCA) is a way of identifying patterns in the correlated data, and expressing the data in such a way so as to highlight their similarities and differences. The main advantage of PCA is that once the Patterns in data have been identified; the data can be compressed, i.e. by reducing the number of dimensions, without much loss of information.
The methods involved in PCA are discussed below:
1. Getting some data
2. Normalization of data
3. Calculation of covariance matrix.
4. Interpretation of covariance matrix.

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relationships through repeated
presentation of data and is capable of
generalizing to new, previously unseen data. For this study, the network is given a set of inputs and corresponding desired outputs, and the network tries to learn the input-output relationship by adapting its free parameters. First, a training input pattern is presented to
the network input layer. The network
then propagates the input pattern from layer to layer until the output pattern is Generated by the output layer. If this pattern is different from the desired output, an error is calculated and then

The research paper published by IJSER journal is about Surface Roughness Optimization Techniques of CNC Milling: A Review 13

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propagated backwards through the network from the output layer to the Input layer.

3. Roughness average technique(Ra)

4. Taguchi and ANOVA technique

RSM

5.

Roughness average (Ra): This parameter is also known as the arithmetic mean roughness value, AA (arithmetic average)
or CLA (center line average). Ra is universally recognized and the most used international parameter Of roughness.
ANOVA can be useful for determining influence of any given input parameter for series of experimental. Result by design of exp. For machining process and it can be to interpret experimental data.
While performing ANOVA degrees of freedom should also be considered together with each sum of square. In ANOVA studies with certain test error, error variance determination is very Important.
These techniques select orders of polynomial model, analysis of points, conduct analysis and model fitting.

Table No. 4 Detailed Description of Techniques

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Now, we consider the machining parameters that can have a significant effect on surface roughness. So, we have to design a table
showing factors, technique and software
used in each paper. This is done in table 5 to explain the status of each parameter in each of the selected papers.

Table No. 5 showing status of parameters

Most important parameter is feed rate followed by cutting speed and depth of cut. These have a significant effect on the surface roughness. Language tools are being used along with statistical tools for determination of surface roughness.

Three major categories were created to classify the selected papers: These are:

(i) Approaches that are based on machining theory to develop analytical models and/or computer
algorithms to represent the machined surface;
(ii) Approaches that examine the effects of various factors through the execution of experiments and the analysis of the results;
(iii) Approaches that use designed experiments;
(i) It includes approaches that place emphasis on certain aspects from
the theory of machining such as

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The research paper published by IJSER journal is about Surface Roughness Optimization Techniques of CNC Milling: A Review 15

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process kinematics, cutting tool properties, chip formation mechanism etc. Computer-aided design (CAD) methods and tools are utilized so as to achieve the goal of building a model that will be able to simulate the creation of the machined surface profile, thus visualizing surface topography and assessing surface roughness. In general, geometric model development forms the basis of the approach through rigorous mathematical equations. This model is then implemented by a computer algorithm in order to handle the complex calculations. The vibration frequency ratio (FR), which was defined as the ratio of vibration frequency (in Hz) over spindle rotational speed (in rps), was thought to influence the period of the surface waviness along the axial direction. It was also found that the effects of the radial direction vibrations on the surface roughness measures were much more significant than those of either the tangential direction vibrations or the axial direction vibrations as
would be expected.
(ii) The experimental approach may be thought of as the most ‘obvious’ method: experiments with the factors that are considered to be the most important are conducted and the obtained results are used to investigate the effect of each factor as well as the influencing mechanism on the observed quality characteristic. Regression analysis is often employed in order to build models based on the experimental data. The researcher’s intuition and insight play a great role in this approach but a high understanding of the examined phenomenon is also necessary for the experiment to yield any meaningful results. The experimental approach is mainly adopted in cases where there can be no analytical formulation of the cause and effect relationships between the various factors. The experimental study included accurate characterization of the edge geometry so as to measure edge features, experimentation on a rigid machine tool with good spindle accuracy to minimize vibration and analysis of variance to establish the
statistical significance of the

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(iii)
parameters. The findings revealed the significant effects of the edge hone radius and the work piece hardness to surface roughness and cutting forces.
The reason why designed
optimization is not completely explained.

Conclusion:

 Range of the process parameters can be established with the help of review done on surface roughness
optimization.
experiments were classified under a
different category from the previous approaches is because they constitute a systematic method concerning the planning of experiments, collection and analysis of data with near-optimum use of available resources.

Gaps in existing Literature:

 Most of the researchers have investigated only limited number of process parameters of CNC milling.
 Multi - response optimization of parameters of CNC milling is another area where less attention has been paid in the past.
 The optimization techniques have not been completely explained.
 A limited work is done on modeling of parameters.
 A large number of materials are yet to be verified by experimentation.
 Difference between single response
optimization and multi response
 Effect of process parameters like cutting speed, feed rate, lubrication pressure, depth of cut on surface roughness were studied.
 Taguchi Technique can be used for optimization of parameters for surface roughness.
 Response Surface Methodology (RSM) can be used for developing mathematical models in the form of regression equations.
 For single- response optimization, desirability function can be used in combination with RSM.
 For multi-response optimization utility concept can be used along with Taguchi Technique.
 Surface Roughness can be compared both experimentally and mathematically.
 Some papers with more number of parameters can be selected.

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 Difference between single response optimization and multi response optimization can be worked out.
 Experimental methods are preferred as compare to analytical methods for analysis.
 Various techniques like Graph
theories can be explored.

References:

 H.Oktem, H.Kurtaran, (2005) “Application of response surface methodology in the optimization of cutting conditions for surface roughness”, Journal of Material Processing Technology 170, Pp. 11–16.
 Julie Zhang, Joseph Chen (2007) “Surface Roughness optimization in an end milling operation using Taguchi design method”, Journal of Material Processing Technology 184, 233-239.
 Oguz Colak, Cahit Kurbanoglu (2007) “Milling Surface Roughness using evolutionary programming methods”, Journal of Materials & Design 28, 657-
666.
 Cevdut Gologlu, Nazim Sakarya (2008) “The effects of cutter path strategies on surface roughness of pocket milling of
1.2738 steel based on Taguchi method”, Journal of Material Processing Technology 206, 7-16.
 Sanjit Moshat et al (2010) “Optimization of Cnc end milling process parameters using PCA based Taguchi Method”, International Journal of Engineering, Science & Technology, 92-102.
 M.F.F.Ab.Rashid et al (2010) “Surface Roughness Prediction for CNC milling process using Artificial Neural Network”, Proceedings of World
Congress in Engineering.

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