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					International Conference on Science, Technology and Innovation for Sustainable Well-Being
(STISWB), 23-24 July 2009, Mahasarakham University, Thailand

       Application of Response Surface
     Methodology in cylindrical grinding of
          metal matrix composites
                       *Raviraj Shetty , R.Nayak, Laxmikanth G.Keni

                  Department of Mechanical and Manufacturing Engineering
          Manipal Institute of Technology, Manipal University, Karnataka, INDIA
                               E-mail: rrshetty2@rediffmail.com

                                      Dr.Raviraj Shetty
                  Department of Mechanical and Manufacturing Engineering
          Manipal Institute of Technology, Manipal University, Karnataka, INDIA


In this paper, the effects and the optimization of machining parameters on surface roughness
in the cylindrical grinding of 6061Al-SiC25P (MMCs) are investigated. In the grinding process,
a machining parameter, such as hardness, flow rate and depth of cut were chosen for
evaluation by the response surface methodology. By response surface methodology, a
complete realization of the process parameters and their effects were achieved. The variation
of surface roughness with machining parameters was mathematically modeled using response
surface methodology. Finally, experimentation was carried out to identify the effectiveness of
the proposed method.

Keywords: Metal matrix composites, Surface roughness, Response surface methodology.

1. Introduction                                  The main concern when machining MMC is
   Reinforced metal matrix composites            the extremely high tool wears due to the
(MMCs) offer advantages in applications          abrasive action of the ceramic fibres or
where good capability to withstand               particles. Therefore, materials of very high
relatively high temperature is needed,           resistance     to   abrasive    wear,     like
besides the requirements of high specific        polycrystalline diamond tipped tools
strength and stiffness, which are typical        (PCDs), are often recommended [3-8].
features of composite materials. MMCs are        Tungsten carbide tools are not effective for
often fabricated with near-net-shape             the machining of these materials and their
processing techniques both traditional, such     use should be limited to cases where
as precise casting and forging [1], and          diamond tipped tools are not available, such
innovative, such as a variety of spray           as for twist drills and taps with diameter
techniques [2]. However, a number of             lower than 3 mm [4]. Recently, a special
secondary machining operations is always         tool fixturing which minimizes the sliding of
necessary.                                       the hard particles against the tool faces has
                                                 been proposed and it has been shown that

International Conference on Science, Technology and Innovation for Sustainable Well-Being
(STISWB), 23-24 July 2009, Mahasarakham University, Thailand

the wear resistance of tungsten carbide tools    Temperatures were accurate to within ±2oC
can be enhanced up to values comparable to       and quench delays in all cases were within
diamond tools [5]. The grinding of MMCs          20s. After solutionising, the samples were
has received little attention. To the authors'   water quenched to room temperature, and
knowledge there is one paper ceiling with        subsequently aged for six different times to
the grinding of Al2O3 short fibre reinforced     obtain optimum peakage and over age time
MMCs [9]: the main results are the               and      according      to     macrohardness
independence of the surface finish of the        measurement 2 and 24 h were accepted as
grinding parameters and the superiority of       peak-aging        and     over-aging      time
diamond      and     CBN       wheels    over
                                                 respectively. All aged and solutionized
conventional abrasives. Another paper
                                                 samples were kept in a refrigerator right
focuses on the necessity of using grinding
                                                 after the heat treatments. In order to observe
wheels for the removal of gates in MMC
castings [10]. The machining guidelines of       the effect of matrix hardness on grinding of
one producer of MMCs provide some                the composite materials three samples had
indications on grinding wheels [11]. As is       been selected Table I. A cross-section of an
well known, the grinding process does not        6061 Al MMCs specimen composite
perform very well for soft materials due to      material shown in Fig I. The selected
the tendency of the chips to clog the wheel.     experimental material was manufactured by
However, the grinding process plays an           stir casting process. The chemical
important role in secondary machining            composition of specimens is given in Table
operations on MMC parts due to the free          II. Grinding method as machining process
cutting tendency of these materials [3]. The     was selected. The experimental study
grinding process might also be possible in       carried out in cylindrical grinding machine.
heavy-duty grinding operations, where a          Surface condition of machined workpiece
single grinding process could be economic,       was observed using JEOL JSM-6380LA
which eliminates the need for prior metal        Analytical scanning electron microscope.
cutting processes [12].                          Surface roughness was measured using
In this work an experimental investigation       Taylor/Hobson surtronoic 3+ surface
was performed in order to assess some            roughness measuring instrument in Fig II.
grinding characteristics of MMCs.
                                                 Experimental setup of cylindrical grinding
                                                 process is shown in Fig III.
2. Experimental
                                                 Table I. The Heat treatment conditions and
  Al–SiC MMC workpiece specimens                 Hardness results
having aluminum alloy 6061 as the matrix
                                                   Heat    Solution   Quench     Aging        Hardne
and containing 15 vol. % of silicon carbide      treatme   treatme    conditi   treatme         ss
particles of mean diameter 25µm in the              nt        nt        on         nt         [BHN]
form of cylindrical bars of length 120mm            As-        -         -        Non-          68
and diameter 20mm is manufactured in             Extrude                          aged
Vikram Sarbhai Space Centre(VSSC)                  Aged      1h at     Water      2h at         94
Trivandrum by Stir casting process with           for 2h    5400C      quench    2200C
pouring temperature 700-710°C, stirring rate       (PA)                  at
195rpm, extrusion at 457°C,extrusion ratio                             2000C
                                                  Aged       1h at     Water     24h at         81
30:1, direct extrusion speed 6.1m/min to         for 24h    5400C      quench    2200C
produce Ø40mm cylindrical bars. The               (OA)                   at
specimens were solution treated for 2 hr at a                          2000C
temperature of 540oC in a muffle furnace;

International Conference on Science, Technology and Innovation for Sustainable Well-Being
(STISWB), 23-24 July 2009, Mahasarakham University, Thailand

                                                      models making it feasible to do prediction in
                                                      function of operation conditions [13].
                                                      Response surface methodology (RSM) is a
                                                      collection of mathematical and statistical
                                                      techniques that are useful for the modeling
                                                      and analysis of problems in which a response
    Fig I A cross-section of an 6061 Al MMCs
                     specimen                         of interest is influenced by several variables
                                                      and the objective is to optimize this response
Table II. Nominal chemical composition of Base          In many engineering fields, there is a
metal (6061 Al alloy)                                 relationship between an output variable of
                                                      interest „y‟ and a set of controllable
 Element        Cu     Mg    Si      Cr       Al
 Weight.        0.25   1.0   0.6    0.25    Balance
                                                      variables {x1, x2 . . . .xn}. In some systems,
percentage                                            the nature of the relationship between y and
                                                      x values might be known. Then, a model can
                                                      be written in the form

                                                        y  f ( x1 , x2 ,...., xn )           (1)
                                                      where ε represents noise or error observed in
                                                      the response y. If we denote the expected
                                                      response be
                                                         E ( y )  f ( x1 , x2 ,...., xn )  y
                                                                                             ˆ  (2)
                                                         then the surface represented by
                                                         y  f ( x1 , x2 ,...., xn )
                                                         ˆ                                      (3)
                                                      is called response surface. In most of the
             Fig II Roughness measurement equipment   RSM problems, the form of relationship
                                                      between the response and the independent
                                                      variable is unknown. Thus the first step in
                                                      RSM is to find a suitable approximation for
                                                      the true functional relationship between y
                                                      and set of independent variables employed.
                                                      Usually a second order model is utilized in
                                                      response surface methodology [15].
                                                                    k            k
                                                         y     x    x 2     x x    (4)
                                                              o          i i          ii i           ij i   j
                                                                  i 1         i 1          i   j
        Fig III Roughness measurement equipment
                                                        The β coefficients, used in the above
       Response surface methodology                   model can be calculated by means of using
The surface finish of machined surface is             least square method. The second-order
important in manufacturing           engineering      model is normally used when the response
Applications which have considerable effect           function is not known or nonlinear.
on some properties such as wear resistance,
light reflection, heat transmission, coating and      3. Results and Discussions
resisting fatigue. While machining, quality of
the parts can be achieved only through proper         The orthogonal array for two factors at three
cutting conditions. In order to know the              levels was used for the elaboration of the
surface quality and dimensional properties in         plan of experiments the array L27 was
advance, it is necessary to employ theoretical

International Conference on Science, Technology and Innovation for Sustainable Well-Being
(STISWB), 23-24 July 2009, Mahasarakham University, Thailand

selected, which has 27 rows corresponding        of confidence of 95%. From the analysis of
to the number of tests (26 degrees of            Table V, it is apparent that, the F (calculated
freedom) with 13 columns at three levels.        value) is greater than the F-table value (F
The factors and the interactions are assigned    0.05, 9, 10=3.02) and hence the second order
to the columns. The first column was             response function developed is quiet
assigned to the Hardness(BHN) (A), the           adequate.
second column to Depth of cut mm (B), the          Table V: ANOVA table for response function of
fifth column to the Flow rate ml/min(C) and      the surface roughness
remaining were assigned to interactions. The
output to be studied was the surface             Source
                                                                   Seq SS         Adj MS   F        P
roughness. The selected levels and factors in    Regression   9    0.8831         0.098    91.51   0.00
machining of MMCs are shown in Table IV.         Residual
                                                              10   0.0107         0.001
                                                 Total        19   0.8939
Table IV: Levels and factors

             (A)        (B)         (C)
                                                 Contour plot of surface roughness at
          Hardness   Depth of      Flow
           (BHN)     cut(mm)    rate(ml/min)
                                                 hardness- flow rate planes at different depth
   1         68        0.04         780
                                                 of cut are shown in Fig IV. These response
   2         81        0.06        1080          contours can help in the prediction of the
   3         94        0.08        1380
                                                 surface roughness at any zone of the
                                                 experimental domain. It is clear from these
         Response surface analysis
                                                 figures that the surface roughness decreases
  The second order response surface
                                                 with the increase of hardness.
representing the surface roughness (Ra) can
be expressed as a function of cutting
parameters such as (A) Hardness (BHN),
(B) Depth of cut (mm), and (C) Flow rate
(ml/min). The relationship between the
surface    roughness      and    machining
parameters has been expressed as follows:

  From the observed data for surface
roughness, the response function has been
determined in uncoded units as:
  Ra = 7.76969- 0.119088A - 7.86757B -
0.00101748C + 0.000513717A2 -7.95455B2
- 3.13131X10-07C2 + 0.0240385AB +
1.37821X10-05AC + 0.00312500BC

  Result of ANOVA for the response
function surface roughness is presented in
Table V. This analysis is carried out for a
level of significance of 5%, i.e., for a level

International Conference on Science, Technology and Innovation for Sustainable Well-Being
(STISWB), 23-24 July 2009, Mahasarakham University, Thailand

                                                      A second-order response surface model
                                                     for surface roughness has been developed
                                                     from the observed data. The predicted and
                                                     measured values are fairly close, which
                                                     indicates that the developed model can be
                                                     effectively used to predict the surface
                                                     roughness on the machining of MMCs with
                                                     95% confidence intervals. Using such
                                                     model, one can obtain a remarkable savings
                                                     in time and cost.

                                                     5. References

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                                                     [2] T. S. Srivatsan and E. J. Lavernia,
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                                                        matrix      composites      using    spray
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                                                        (edited by T. S. Srivatsan and S.
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International Conference on Science, Technology and Innovation for Sustainable Well-Being
(STISWB), 23-24 July 2009, Mahasarakham University, Thailand

   Analysis         Machinability          and
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