STAINLESS STEEL by iaemedu

VIEWS: 3 PAGES: 11

									       INTERNATIONAL Engineering and Technology (IJMET), ISSN
International Journal of Mechanical JOURNAL OF MECHANICAL 0976 –
6340(Print), ISSN 0976 – 6359(Online) Volume 3, Issue 1, January- April (2012), © IAEME
         ENGINEERING AND TECHNOLOGY (IJMET)
ISSN 0976 – 6340 (Print)
ISSN 0976 – 6359 (Online)
Volume 3, Issue 1, January- April (2012), pp. 150-160
                                                                     IJMET
© IAEME: www.iaeme.com/ijmet.html
Journal Impact Factor (2011): 1.2083 (Calculated by GISI)       ©IAEME
www.jifactor.com




     ENHANCEMENT OF SURFACE ROUGHNESS OF 316L
  STAINLESS STEEL AND TI-6AL-4V USING LOW PLASTICITY
              BURNISHING: DOE APPROACH
                     U. D. Gulhane1*, S. B. Mishra2, P. K. Mishra2
   1
    Research Scholar, Department of Mechanical Engineering, Motilal Nehru National
                 Institute of Technology, Allahabad (U.P.)-211004, India
     1
       Department of Mechanical Engineering, Finolex Academy of Management and
                       Technology, Ratnagiri (M. S.) -415639, India
2
  Department of Mechanical Engineering, Motilal Nehru National Institute of Technology,
                              Allahabad (U. P.)-211004, India
           *Corresponding author, Asst. Professor, Dept. of Mechanical Engg.,
   Finolex Academy of Management and Technology, P-60/61, MIDC, Mirjole Block,
               RATNAGIRI- (M.S.) 415639, India, Tel.: +91-9226797252,
             Fax: +91-02352228436, E-mail ID: umesh_gulhane@yahoo.com


ABSTRACT
        In the present work, effect of Low Plasticity Burnishing (LPB) parameters in
improving surface roughness of 316L Stainless Steel and Ti-6Al-4V have been
investigated. Full factorial design of experiment (DOE) have been used to visualize the
effect of LPB process parameters such as speed, pressure, ball diameter and number of
passes on surface roughness. The signal-to-noise (S/N) ratio and ANOVA was carried out
to identify the significant LPB parameters. The percentage improvement in surface
roughness is found to be 87 % and 85 % for Ti-6Al-4V and 316L Stainless Steel
respectively. Empirical relations have been developed for LPB parameters and the
surface roughness.

Keywords: Low Plasticity Burnishing (LPB), Surface roughness, Design of experiment
(DOE), 316 L Stainless Steel, and Ti-6Al-4V




                                          150
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online) Volume 3, Issue 1, January- April (2012), © IAEME
     1. INTRODUCTION
         Artificial joints surgery is becoming more common in the younger to older age
patients due to change in lifestyle [1]. Metallic Biomaterials like 316L Stainless Steel and
Ti-6Al-4V alloy are commonly used for the implants of these artificial joints [2-3]. The
life of such artificial joints is limited by failure due to wear [4]. Wear of the implants are
influence by multiple factors such as material, contact stresses, surface hardness, surface
roughness etc.[5]. Amongst these factors, surface roughness can be enhanced by various
surface enhancement methods. Some of the recent and relevant methods are conventional
burnishing, shot peening, laser peening, water peening, liquid jet peening, low stress
grinding, surface coating, and LPB [6]. Out of these, LPB is a rapid and inexpensive
surface enhancement method [7]. LPB technology enhances the surface roughness [8].
         The principle of the burnishing process is based on plastic deformation of the
surface of work piece by applying external force through a polished ball [9]. The
extensive plastic flow during burnishing of the material leads to considerable
improvement in the surface roughness [10].
         According to Seemikeri et al. (2008) and Hassan (1997) the parameters that have
greater influence on the surface roughness of the material are burnishing speed, pressure,
ball diameter and number of passes[6][9].
         Hassan (1997) investigated the effect of burnishing force and number of
burnishing tool passes on the surface roughness of a commercially available aluminum
and brass. He obtained 85 to 95 % improvement in surface roughness by the application
of burnishing [9]. Hassan et al. (1998) established a mathematical model to relate the
surface roughness with burnishing force and number of tool passes on brass material.
With this mathematical model, they obtained 97 % improvement in surface roughness
with burnishing force of 203 N and two passes of the burnishing [11]. Seemikeri et al.
(2008) have developed a mathematical expression for surface roughness of AISI 1045
work material and obtained 87 % improvement in surface rougness [6].
         The aim of the present work is to investigate the effect of LPB parameters such as
burnishing speed (rotational speed of workpiece) (S), burnishing pressure (P), diameter of
ball (D) and number of passes (N) on surface surface roughness of Ti-6Al-4V and 316L
stainless steel. Other burnishing parameter such as feed being kept constant.
2. MATERIALS AND METHODS
         2.1 Work material
         Nominal and actual compositions of as received 316L stainless steel and Ti-6Al-
4V are shown in Table 1 and 2 respectively. Cylindrical specimens of 9 mm diameter
were prepared from the rods of the material. The initial average surface roughness of Ti-
6Al-4V and 316L stainless steel was 1.88 µm (Ra) and 1.62 µm (Ra) respectively.
Table 1- Composition of 316L SS

   SAE                                    %
               % Cr     % Ni      %C               % Si   %P       %S      Other %Mo
Designation                               Mn

  316L SS                         0.03    2.0      1.0    0.045    0.03
               16–18    10–14                                              2.0–3.0
 (Nominal)                        Max     Max      Max    Max      Max
  316L SS
               17.34    10.69     0.024   1.748    0.471 0.034     0.018   2.08
  (Actual)


                                             151
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online) Volume 3, Issue 1, January- April (2012), © IAEME

Table 2- Composition of Ti-6Al-4V
    SAE
                %Al      %V        %Fe      %Ti     % Sn
 Designation

  Ti-6Al-4V     6.25     4.28     0.214     90       0.38
  (Nominal)     Max      Max      Max       Max      Max
  Ti-6Al-4V
                6.24     3.87     0.192     88.9    0.367
   (Actual)

2.2 Low Plasticity Burnishing Tool
        Low Plasticity Burnishing was carried out using a LPB tool as shown in Fig. 1. It
is comprised of a ball supported in a ball-seat with an arrangement to float the ball of
diameter 8 to 12 mm. The ball is loaded normal to the surface of a specimen. As the ball
rolls over the surface of the specimen, plastic deformation occurs. The pressure is applied
on the ball by pressurized cylinder.
        The LPB tool is held in the tool post of a lathe machine and specimen is held in a
three-jaw chuck [12]. The rotational speed of specimen (burnishing speed) is controlled
by controlling the speed of the chuck.




                       (a)                                                 (b)

                Fig.1. (a) LPB tool (b) Schematic sketch of LPB process

2.3 Design of experiment
       Design of experiments (DOE) was done using full factorial [2k] where k is
number of parameters at two level, to study the effect of LPB process parameters such as
burnishing speed (S), burnishing pressure (P), diameter of ball (D) and number of passes
(N) on surface roughness.
       The quality characteristic is measured by obtaining the S/N characteristics
formulated for surface roughness i.e. Lower-the-better is given by.
                      S/N= -10 log (1/n Σ y2) ---------(1)
Where, y is observed data, and n is number of observations [13].



                                           152
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online) Volume 3, Issue 1, January- April (2012), © IAEME
        Analysis of variance (ANOVA) is carried out using ANOVA module of Minitab
software to investigate design parameters that significantly affect the surface roughness.
        Correlations of surface roughness for both the materials have been obtained by
developing regression models using Microsoft Analyze-it software. For this analysis, a
log transformed response variable and process parameters were calculated by using the
model suggested by Mahagaonkar et al., (2008).
        ln (Y) = β0 + β1 ln(S) + β2 ln (P) + β3 ln(D)+β4 ln(N)---------------------(2)
        Whereβ0, β1, β2, β3, and β4 are the regression coefficients to be determined and
Y is the surface roughness [14].

2.4 Measurement of surface roughness and SEM Analysis,
       The surface roughness (Ra, Arithmetic average) of all the specimens have been
measured by Mitutoyo surface test SJ-400 with cut off value of 4.0 mm. An average of
three measurements was taken for each specimen. SEM studies of the unburnished and
burnished surfaces of 316L stainless steel and Ti-6Al-4V have been conducted using
JEOL JSM-6380A analytical scanning electron microscope.

3. Results and discussion

      Preliminary experiments have been conducted to select the levels of each
parameter by varying each parameter individually and keeping others at minimum level.
The LPB parameters and their levels are shown in Table 3.
                     Table 3-LPB parameters and their levels.
                LPB Parameter               Level 1       Level 2
                Burnishing speed (S)        50 rpm        900 rpm
                Burnishing pressure (P)     0.5 MPa       1.9 MPa
                Ball diameter (D)           8 mm          12 mm
                Number of passes (N)        1             2


   3. 1 Design and Analysis of LPB process parameter

       Design of experiments has been used to study effect of four burnishing parameters
at two levels on surface roughness. In this study, L16 orthogonal array is employed to
obtain the experimental results for surface roughness of both the materials by varying
speed(S), pressure (P), diameter of ball (D) and number of passes (N). Table 4 shows the
experimental design matrix, response variables and calculated S/N ratio for surface
roughness of Ti-6Al-4V and 316L SS.




                                           153
              International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
              6340(Print), ISSN 0976 – 6359(Online) Volume 3, Issue 1, January- April (2012), © IAEME
              Table 4 Experimental design matrix, response variables and S/N ratio.

              Low plasticity burnishing           Surface Roughness Ra (µm)          Surface Roughness Ra (µm)
                    parameters                             Ti-6Al-4V                          316L SS                   Calculated S/N
                                                                                                                        ratio for surface
Expt.                        Ball                                                                                      roughness using
        Speed     Press.              No. of
 No.                         dia.                                                                                         equation (1)
        ( rpm)    (MPa)               Passes      R1      R2      R3     Ravg        R1       R2     R3      Ravg
                            (mm)
                                                                                                                      Ti-6Al-    316L
          S          P       D           N
                                                                                                                      4V         SS
 1       50         0.5      8           1        0.53    0.55    0.54   0.540       0.54     0.53   0.54    0.537    5.351      5.406
 2       50         0.5      8           2        0.52    0.50    0.51   0.510       0.51     0.52   0.51    0.513    5.847      5.792
 3       50         0.5      12          1        0.42    0.41    0.41   0.413       0.46     0.45   0.47    0.460    7.673      6.743
 4       50         0.5      12          2        0.39    0.40    0.39   0.393       0.41     0.43   0.41    0.417    8.104      7.602
 5       50         1.9      8           1        0.59    0.58    0.59   0.587       0.52     0.54   0.53    0.530    4.632      5.513
 6       50         1.9      8           2        0.31    0.32    0.31   0.313       0.42     0.43   0.42    0.423    10.079     7.466
 7       50         1.9      12          1        0.35    0.36    0.34   0.350       0.39     0.40   0.41    0.400    9.116      7.957
 8       50         1.9      12          2        0.30    0.31    0.32   0.310       0.38     0.39   0.38    0.383    10.170     8.328
 9       900        0.5      8           1        0.56    0.54    0.54   0.547       0.53     0.52   0.54    0.530    5.244      5.513
 10      900        0.5      8           2        0.50    0.51    0.49   0.500       0.41     0.42   0.42    0.417    6.019      7.604
 11      900        0.5      12          1        0.42    0.42    0.43   0.423       0.43     0.44   0.43    0.433    7.466      7.263
 12      900        0.5      12          2        0.38    0.38    0.39   0.383       0.37     0.38   0.36    0.370    8.328      8.634
 13      900        1.9      8           1        0.52    0.53    0.53   0.527       0.49     0.50   0.48    0.490    5.569      6.195
 14      900        1.9      8           2        0.31    0.30    0.30   0.303       0.25     0.24   0.25    0.247    10.361     12.156
 15      900        1.9      12          1        0.49    0.48    0.49   0.487       0.41     0.42   0.41    0.413    6.255      7.673
 16      900        1.9      12          2        0.24    0.25    0.24   0.243       0.35     0.34   0.35    0.347    12.274     9.201

              Optimum level of parameter for surface roughness is evaluated using S/N ratio of Table 4
              and reported in Table 5. Optimum level of parameters for surface roughness of Ti-6Al-
              4V in the decreasing order of importance are N2-D2-P2-S2 i.e. Number of passes (2),
              ball diameter (12mm), pressure (1.9 MPa), and speed (900rpm). Whereas that for 316L
              SS in decreasing order of importance are N2-P2-S2-D2.i.e. Number of passes (2),
              pressure (1.9 MPa), speed (900rpm) and ball diameter (12mm). Table 5 also indicates the
              higher values of delta for number of burnishing passes (N) for both the materials
              suggesting its significant contribution towards surface roughness.
              Table 5- Significance of LPB Parameters for surface roughness.
                                     Response table for S/N Lower is better
                                              Ti-6Al-4V                                       316L SS
               Parameters             Level                                           Level
                                                       Delta     Rank                                Delta     Rank
                                  1           2                                  1            2
                    S        7.622       7.69* 0.068       4         6.851                  8.03*    1.179      3
                    P        6.754       8.557* 1.803      3         6.82                   8.061*   1.242      2
                    D        6.638       8.673* 2.035      2         6.956                  7.925*   0.97       4
                    N        6.413       8.898* 2.484      1         6.533                  8.348*   1.815      1
                                            * Optimized level of parameter


                                                                   154
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online) Volume 3, Issue 1, January- April (2012), © IAEME
        Table 6 and 7 show the ANOVA results for the surface roughness of Ti-6Al-4V
alloy & 316L stainless steel respectively. Statistically, there is a tool called as F test
named after Fisher to see which design parameter have a significant effect on quality
characteristics [15]. Higher F-values of 21.93 and 13.08 for number of passes of Ti-6Al-
4V and 316L stainless steel respectively suggest its significant contribution on surface
roughness. From Table 6, LPB process parameters for Ti-6Al-4V can be arranged in the
decreasing order of importance as N-D-P-S. After number of passes, diameter of
burnishing ball plays important role for improving surface roughness of Ti-6Al-4V.
Larger ball diameter indicates the larger contact area between the LPB tool and the
specimen surface, thus diminising burnishing pressure [10]. Burnishing pressure is the
third important parameter and speed is fourth. This suggests that for Ti-6Al-4V to
improve surface roughness higher number of passes is required with larger ball diameter.
Whereas those for 316L stainless steel in the decreasing order of importance are N-P-S-D.
After number of passes, pressure plays important role in improving surface roughness of
316L SS. This suggests that in improving surface roughness of 316L SS higher number
of passes are required at higher pressure.
        These results obtained through ANOVA are in close agreement with Taguchi
method. For Ti-6Al-4V, burnishing pressure and number of burnishing passes (P*N)
indicate strong interaction. Whereas for 316L SS, burnishing speed and number of
burnishing passes(S*N) show strong interaction.

Table 6 ANOVA results for signal-to-noise ratio for surface roughness of Ti-6Al-4V.

Source           DF    Seq. SS       Adj SS       Adj Ms        F        P
S                1     0.0184        0.0184       0.0184        0.02     0.903
P                1     12.9997       12.9997      12.9997       11.55    0.019
D                1     16.573        16.573       16.573        14.72    0.012
N                1     24.6903       24.6903      24.6903       21.93    0.005
S*P              1     0.0091        0.0091       0.0091        0.01     0.932
S*D              1     0.2562        0.2562       0.2562        0.23     0.653
S*N              1     1.5754        1.5754       1.5754        1.40     0.290
P*D              1     0.2337        0.2337       0.2337        0.21     0.668
P*N              1     13.5925       13.5925      13.5925       12.07    0.018
D*N              1     0.618         0.618        0.618         0.55     0.492
               5       5.6297        5.6297       1.1259
Residual Error
Total          15      76.196

Table 7- ANOVA results for signal-to-noise ratio for surface roughness of 316L SS.
 Source      DF Seq. SS           Adj SS         Adj Ms        F        P
 S           1     5.5610         5.5610         5.5610        5.52     0.066
 P           1     6.1663         6.1663         6.1663        6.12     0.056
 D           1     3.7606         3.7606         3.7606        3.73     0.111
 N           1     13.1727        13.1727        13.1727       13.08    0.015
 S*P         1     0.3875         0.3875         0.3875        0.38     0.562

                                          155
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online) Volume 3, Issue 1, January- April (2012), © IAEME
 S*D               1     1.6581          1.6581         1.6581         1.65         0.256
 S*N               1     3.4060          3.4060         3.4060         3.38         0.125
 P*D               1     1.0502          1.0502         1.0502         1.04         0.354
 P*N               1     1.6297          1.6297         1.6297         1.62         0.259
 D*N               1     2.4510          2.4510         2.4510         2.43         0.179
 Residual          5     5.0353          5.0353         1.0071
 Error
 Total             15    44.2785

3.2 Quantification of surface roughness
        Surface roughness and LPB process parameters from Table 4 were calculated to
logscale. Correlations of surface roughness for both the materials have been obtained by
developing regression models suggested by Mahagaonkar et al., (2008) as shown in
equation(2) [14]. Intercepts and coefficients for surface roughness for Ti-6Al-4V and
316L SS are calculated using Microsoft Analyze-it software are shown in Table 8 and 9
respectively. Equation (3) and (4) gives approximate values of the surface roughness for
the Ti-6Al-4V and 316L SS respectively.

Table 8- Intercepts and coefficient for surface roughness for Ti-6Al-4V.
 Term          Coefficient        SE         P          95% CI of coefficient
 Intercept     0.5912             0.4850     0.2483     -0.4762      to 1.6586
 ln(S)         -0.0027            0.0281     0.9255     -0.0646      to 0.0592
 ln(P)         -0.1555            0.0609     0.0268     -0.2895      to -0.0215
 ln(D)         -0.5781            0.2004     0.0149     -1.0192      to -0.1369
 ln(N)         -0.4127            0.1172     0.0048     -0.6708      to -0.1547

Surface roughness (Ra) = 1.8061 (S)-0.0027 (P)-0.1555 (D)-0.5781 (N)-0.4127 -----------------(3)

Table 9- Intercepts and coefficient for surface roughness for 316L SS.

 Term          Coefficient         SE         P           95% CI of coefficient
 Intercept     0.1252              0.4094     0.7655      -0.7760      to 1.0264
 ln(S)         -0.0470             0.0237     0.0734      -0.0992      to 0.0053
 ln(P)         -0.1071             0.0514     0.0613      -0.2202      to 0.006
 ln(D)         -0.2754             0.1692     0.1318      -0.6479      to 0.097
 ln(N)         -0.3014             0.0990     0.0111      -0.5193      to -0.0836

Surface roughness (Ra) = 1.1333 (S)-0.0470 (P)-0.1071 (D)-0.2754 (N)-0.3014    --------------
                                                                                                (4)

    From above correlations, it is clear that higher number of passes is required with
larger ball diameter to improve surface roughness of Ti-6Al-4V. Whereas for improving
surface roughness of 316L SS number of passes are required at higher pressure.


                                                 156
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online) Volume 3, Issue 1, January- April (2012), © IAEME
   3.3 Experimental evaluation of Surface roughness
       Fig. 2 shows the surface roughness plots for burnished and unburnished alloys.
The Burnished Ti-6Al-4V show surface roughness of 0.24µm with burnishing parameter
S2-P2-D2-N2 (i.e. Speed of 900 rpm, pressure of 1.9 MPa, Ball diameter of 12mm and 2
numbers of passes), whereas the burnished 316L SS shows surface roughness of 0.25µm
Ra with burnishing parameter S2-P2-D1-N2. (i.e. Speed of 900 rpm, pressure of 1.9
MPa, Ball diameter of 8mm and 2 numbers of passes).

   Unburnished
   Ti-6Al-4V,
   Ra (1.88µm)

    Burnished
    Ti-6Al-4V,
   Ra (0.24µm)
Burnished parameter
   S2-P2-D2-N2

Unburnished 316L
       SS,
  Ra (1.62µm)


Burnished 316L SS,
   Ra (0.25µm)
Burnished parameter
   S2-P2-D1-N2


Fig 2. The surface roughness plots for burnished and unburnished Ti-6Al-4V and 316L
SS.

        SEM analyses of the unburnished and burnished samples have been carried out to
understand the morphology of unburnished and burnished surfaces and the material
redistribution mechanism. SEM micrographs of the initial turned surfaces (i.e.
unburnished samples) of the materials 316L SS and Ti-6Al-4V are shown in Figs. 3 and 4
respectively. Turning directions are indicated by the arrow mark at the corner of the
images. SEM images of the unburnished 316L SS and Ti-6Al-4V show the rough surface
with machining marks, asperities and grooves. Marks 'A', 'E 'and 'D' (Figs. 3 and 4)
indicates the sharp asperities that adhere to the surfaces during turning operation. Figure
5 and 6 are the SEM micrographs of the burnished samples of 316L SS and Ti-6Al-4V
respectively. From the SEM images, it can be observed that the surfaces become
smoother and uniform with the burnishing operation. Ball burnishing directions are
shown by the arrow mark at the corner of images. Marks 'B' and 'G' in Figs. 5 and 6 show
sharp machining marks deformed due to ball burnishing. According to Low and Wong
(2011), when the surfaces are subjected to continuous compressive load during ball
burnishing operation, the sharp asperities deforms, resulting in a smoother and more
uniform surface [10]. SEM images of 316L SS and Ti-6Al-4V also show some of the
undeformed asperities ('C' and 'F' in Figs. 5 and 6 respectively). According to Hassan


                                           157
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online) Volume 3, Issue 1, January- April (2012), © IAEME
(1997), engineering components are usually left with machining marks of irregular
heights and spacing [9].




Fig. 3. SEM image of initial turned surfaces   Fig. 4. SEM image of initial turned
of 316L SS                                     surfaces of Ti-6Al-4V




Fig. 5. SEM image of 316L SS surface           Fig.6. SEM image of Ti-6Al-4V surface
produced by ball burnishing at S=900rpm,       produced by ball burnishing at S=900rpm,
P=1.9 Mpa, D=12 mm, N= 2                       P=1.9 Mpa, D=12 mm, N= 2


CONCLUSIONS

        LPB is an effective process for improving the surface roughness of the Ti-6Al-4V.
Following conclusions can be drawn under the considered burnishing conditions.
         (1) Ti-6Al-4V alloy has shown 87 % improvement in surface roughness over the
initial surface roughness of 1.88 µm whereas 316L Stainless steel has shown 85 %
improvement in surface roughness over the initial surface roughness of 1.62 µm using
LPB tool.
        (2) For Ti-6Al-4V alloy, best process parameters in the decreasing order of
importance are found to be N-D-P-S (i.e. number of passes-ball diameter-pressure-speed),
whereas for 316L SS it is found to be N-P-S-D (i.e. number of passes-pressure-speed-ball
diameter).



                                           158
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online) Volume 3, Issue 1, January- April (2012), © IAEME
        (3) Number of burnishing passes has shown its significant contribution towards
improvement of surface roughness of Ti-6Al-4V alloy and 316L stainless steel.
        (4) To improve surface roughness of Ti-6Al-4V higher number of passes is
required with larger ball diameter, whereas for improving surface roughness of 316L SS
higher numbers of passes are required at higher pressure.
        (5) Empirical correlations of surface roughness for both the studied materials
have been developed. These correlations may serve as a useful guideline for selecting
process parameters in obtaining desired surface roughness for the Ti-6Al-4V alloy and
316L stainless steel.
        Thus, it is suggested that the surface roughness of Ti-6Al-4V alloy and 316L
stainless steel can be enhanced by LPB.

Acknowledgments
       The authors would like to thank Dr. K. L. Asanare, Director, FAMT- Ratnagiri
for providing the LPB tool and other facilities The authors are thankful to Adler
Mediequip Pvt. Ltd., Ratnagiri for providing the materials and facility of surface
roughness testing. The authors also wishes to thanks Vishweswaraya National Institute of
Technology, Nagpur for extending the facility of SEM.

REFERENCES

[1] S. C. Scholes and A. Unsworth, “Wear studies on the likely performance of CFR-
PEEK/CoCrMo for use as artificial joint bearing materials”, J Mater Sci: Mater Med, Vol.
20, pp. 163-170, 2009.
[2] D. Dowson, “Friction and wear of medical implants and prosthetic devices”, In: Blau,
P. J. (Ed.), Friction, Lubrication, and Wear Technology, ASM Handbook, ASM
International, USA, Vol. 18, pp. 656-664, 1992.
[3] U. D. Gulhane, M. Roy, S. G. Sapate, S. B.Mishra, P. K. Mishra, “Influence of
surface treatment of high carbon steel on the reciprocating wear in comparison with the
316 stainless steel”, Proceeding of ASME/STLE International joint Tribology conference
IJTC2009. Memphis, Tennessee USA, October 19-21, 2009, pp. 55- 57.
[4] S. C. Scholes and A. Unsworth, “Pin-on-plate studies on the effect of rotation on the
wear of metal-on-metal samples”, Journal of materials science: Materials in medicine,
Vol. 12, pp. 299-303, 2001
[5] A. Buford and T. Goswami, “Review of wear mechanisms in hip implants: Paper I -
General”, Materials and Designs, Vol. 25, pp. 385-393, 2004.
[6] C. Y. Seemikeri, P. K. Brahmankar, S. B. Mahagaonkar, “Investigations on surface
integrity of AISI 1045 using LPB tool”, Tribology International, Vol. 41, pp. 724– 734,
2008.
[7] P. S. Prevey, “FOD resistance and fatigue crack arrest in low plasticity burnished
IN718”, Proceedings: 5th National turbine engine high cycle fatigue conference, Chandler,
AZ, March 7-9, 2000.
[8] M. A. Hassan and A. M.Maqableh, “The effects of initial burnishing parameters on
non-ferrous components”, Journal of Materials Processing Technology, Vol. 102, pp.
115-121, 2000.



                                          159
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online) Volume 3, Issue 1, January- April (2012), © IAEME
[9] A. M. Hassan, “The effects of ball- and roller-burnishing on the surface roughness
and hardness of some non-ferrous metals”, Journal of Materials Processing Technology,
Vol. 72, pp. 385–391, 1997.
[10] K. O. Low and K. J. Wong, “Influence of ball burnishing on surface quality and
tribological characteristics of polymers under dry sliding conditions”, Tribology
International, Vol. 44, pp. 144-153, 2011.
[11]A. M. Hassan, H. F. Al-Jalil, A. A. Ebied, “Burnishing force and number of ball
passes for the optimum surface finish of brass components”, Journal of Materials
Processing Technology, Vol. 83, pp. 176–179,1998.
[12] D. J. Hornbach, P. S. Prevey, E. F. loftus, “Application of low plasticity burnishing
(LPB) to improve the fatigue performance of Ti-6Al-4V femoral hip stems”, Journal of
ASTM International, Vol. 3, No. 5., 2006, [online] available: www.astm.org [Accessed
Jan 14, 2010].
[13] B. M. Gopalswamy, B. Mondal, S. Ghosh, “Taguchi method and ANOVA: An
Approach for process parameters optimization of hard machining hardened steel”,
Journal of scientific and Industrial Research, Vol. 68, pp. 686-695, 2009
[14] S. B. Mahagaonkar, P. K. Brahmankar, C. Y. Seemikeri, “Effect of shot peening
parameters on micorhardness of AISI 1045 and 316L material: an analysis using design
of experiment”, Int J Adv Manuf Technol, Vol. 38, pp. 563-574, 2008.
[15] W. H. Yang and Y. S. Tarng, “Design optimization of cutting parameters for turning
operations based on the Taguchi method”, Journal of Materials Processing Technology,
Vol. 84, pp. 122–129,1998.




                                           160

								
To top