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					 INTERNATIONAL JOURNAL OF MECHANICAL ISSN 0976 – 6340(Print),
International Journal of Mechanical Engineering and Technology (IJMET), ENGINEERING
ISSN 0976 – 6359(Online), Volume 5, Issue 4, April (2014), pp. 147-152 © IAEME
                            AND TECHNOLOGY (IJMET)

ISSN 0976 – 6340 (Print)
ISSN 0976 – 6359 (Online)                                                        IJMET
Volume 5, Issue 4, April (2014), pp. 147-152
© IAEME: www.iaeme.com/ijmet.asp
Journal Impact Factor (2014): 7.5377 (Calculated by GISI)                   ©IAEME
www.jifactor.com




      COMPARISON FOR SURFACE ROUGHNESS BETWEEN DUPLEX
      TURNING WITH SINGLE TOOL TURNING WITH HELP OF SPSS
                          SOFTWARE

                                    MANISH KUMAR YADAV
                                    Research Scholar, ME Deptt,
                                Sharda University, G.Noida U.P. India




ABSTRACTS

        The present paper attempts to concentrate develop comparison between duplex turning with
single tool turning with help of SPSS software. The present paper will attempt to explain the role of
coefficient of determination, R-Squared which signifies that variance in dependent variable (DV i.e.
Surface Roughness) can be explained more precisely while using duplex machining process as
compared to single machining and also explain adjusted R-square. This paper also tell the effect of
the number of independent variables (IVs) in a multiple regression model makes the R-square larger.

Keywords: Surface Roughness, R-Square.

1. INTRODUCTION

        In manufacturing there are some criteria on the basis of which the various control parameters
can be selected in order to attain the desired level of the surface finish on the material. During actual
machining operation there are various factors which adversely affect the finish and therefore, the
proper methological consideration of these factors appear to be most crucial for achieving the proper
and desired level of surface finish. Preliminary shaping gives an opportunity to provide the proper
and desired shape and is treated as the first step of a manufacturing process. Casting, molding,
forging, welding etc can provide the shape to the material. Further, different machining operation
like turning, shaping, planning, milling, drilling, etc brings the dimensions of the part under
manufacturing to a proper size. In many applications particularly when the part is made of some
brittle material the scratches found on the surface becomes the source of stress concentration and this
may lead to initiation of crack- propagation and finally to the failure of the part while in operation.

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International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print),
ISSN 0976 – 6359(Online), Volume 5, Issue 4, April (2014), pp. 147-152 © IAEME

Therefore it is important to achieve good surface finish of such parts because this improve its
strength as well as the life mostly if the loading condition is dynamic and repeated in nature.

2. LITERATURE REVIEW

        A number of studies have been made to investigate the surface finish. It has been seen that
Lin, W.S. (1) have studied the study of high speed fine turning of austenitic stainless steel. Sze-Wei,
Gan and Han-Seok, Lim and Rahman, M Frank Watt(2) have discussed a fine tool servo system for
global position error compensation for a miniature ultra-precision lathe. Vikram Kumar, CH R. and
Ramamoorthy, B (3) have dealt with Performance of coated tools during hard turning under
minimum fluid application. Further Sharma, D.K. and Dixit, U.S.(4) have compared the dry and air-
cooled turning of grey cast iron with mixed oxide ceramic tool. Go¨kkaya, Hasan and Nalbant,
Muammer(5) have studied The effects of cutting tool geometry and processing parameters on the
surface roughness of AISI 1030 steel. However, Isik, Yahya(6) have investigated the machinability
of tool steels in turning operations. Dhar, N.R_ and Ahmed, M.T. and Islam, S.(7), did an
experimental investigation on effect of minimum quantity lubrication in machining AISI 1040 steel
and Chang, Chih-Wei and Kuo, Chun-Pao (8) have attempted to evaluate surface roughness in laser-
assisted machining of aluminum oxide ceramics with Taguchi method. It is to be noted that all the
above investigators have reported their results for single tool surface finish operation only. And
Yadav, Manish kumar and Sinha, Dr.P.K and Sinha, Dr.Gopal P.(10) did an analysis on single tool
turning with duplex turning. In the proposed work an attempt has been made to compare the effect of
cutting parameters on surface roughness in multi tool turning and single tool turning with the help of
SPSS on AISI-1018.

3. FACTORIAL DESIGN OF EXPERIMENT

        Factorial Design of the experiment is the method to recognize the significant factors in a
process, make out and fix the problem in a practice, and also identify the possibility of estimating
interactions. This is done using a full factorial DOE. A two level factorial DOE has been used. This
means two levels of each factor will be studied at once. If there are K factors that we need to
evaluate in a process we need to run the experiment 2k times. Each factor will have two levels, a
“high” and “low” level.

4. EXPERIMENTATION

       If two tools, both side of the bed on the lathe carriage and mounted in such a way that both
tool moving in one direction then this is term as Duplex attachment or Duplex turning. Duplex
turning provide two tool cutting operation moving in one direction. Experiments are conducted in
accordance with the statistical technique of experimental design.




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International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print),
ISSN 0976 – 6359(Online), Volume 5, Issue 4, April (2014), pp. 147-152 © IAEME

4.1. EXPERIMENTAL SETUP




                      Fig 1: Attachment for Duplex turning on Lathe machine

5. CUTTING PARAMETERS AND TOOL

Feed, Depth of cut, Cutting speed, HSS tool

6. ANALYSIS OF EXPERIMENTAL DATA

            Table 1: Comparison between Single tool and Duplex machining roughness
                S.NO.      Single tool machining            Duplex Machining
                           F       D     S    R1       F          D       S    R2
                  1      0.071    0.8   180   4.3    0.071     0.4+0.4   180   2.7
                  2       0.14    0.8   180   6.3    0.14      0.4+0.4   180   3.8
                  3      0.071    1.4   180   5.9    0.071     0.7+0.7   180   4.3
                  4       0.14    1.4   180   6.0    0.14      0.7+0.7   180   4.0
                  5       .071    0.8   280   4.1    0.071     0.4+0.4   280   2.2
                  6       0.14    0.8   280   5.4    0.14      0.4+0.4   280   3.5
                  7      0.071    1.4   280   5.6    0.071     0.7+0.7   280   3.7
                  8       0.14    1.4   280   5.8    0.14      0.7+0.7   280   3.3


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International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print),
ISSN 0976 – 6359(Online), Volume 5, Issue 4, April (2014), pp. 147-152 © IAEME

                                Tests of Between-Subjects Effects

 Dependent Variable:Roughness_SINGLE
                                         Type III Sum               Mean
 Source                                   of Squares        df      Square        F         Sig.
 Corrected Model                                 4.435a     6           .739       9.240    .247
 Intercept                                     235.445      1        235.445    2943.063    .012
 FEED_SINGLE                                      1.620     1          1.620      20.250    .139
 DEPTH_SINGLE                                     1.280     1          1.280      16.000    .156
 SPEED_SINGLE                                      .320     1           .320       4.000    .295
 FEED_SINGLE * DEPTH_SINGLE                       1.125     1          1.125      14.063    .166
 DEPTH_SINGLE * SPEED_SINGLE                       .045     1           .045        .562    .590
 FEED_SINGLE * SPEED_SINGLE                        .045     1           .045        .563    .590
 Error                                             .080     1           .080
 Total                                         239.960      8
 Corrected Total                                  4.515     7
 a. R Squared = .982 (Adjusted R Squared = .876)

                                Tests of Between-Subjects Effects

 Dependent Variable:ROUGHNESS_DUPLEX
                                          Type III Sum              Mean
 Source                                     of Squares      df      Square         F        Sig.
 Corrected Model                                  3.347a    6           .558      49.593    .108
 Intercept                                        94.531    1         94.531    8402.778    .007
 FEED_DUPLEX                                        .361    1           .361      32.111    .111
 DEPTH_DUPLEX                                      1.201    1          1.201     106.778    .061
 SPEED_DUPLEX                                       .551    1           .551      49.000    .090
 FEED_DUPLEX * DEPTH_DUPLEX                        1.201    1          1.201     106.778    .061
 DEPTH_DUPLEX * SPEED_DUPLEX                        .031    1           .031       2.778    .344
 FEED_DUPLEX * SPEED_DUPLEX                         .001    1           .001         .111   .795
 Error                                              .011    1           .011
 Total                                            97.890    8
 Corrected Total                                   3.359    7
 a. R Squared = .997 (Adjusted R Squared = .977)

7. RESULT AND DISCUSSION

        So in case of single machine experiment the coefficient of determination, R squared=98.2%,
whereas in case of duplex machine experiment R squared =99.7%.Which signifies that variance in
dependent variable (DV i.e. Surface Roughness) can be explained more precisely while using duplex
machining process as compared to single machining.
        One important indicator which suggest that duplex machining procedure more appropriately
explained the roughness, is adjusted R-square.
        The number of independent variables (IVs) in a multiple regression model makes the R-
square larger. Hence R square increases because of the total number of IVs and not because of added
IVs is a good predictor of DV. To address such effects adjusted R-square is considered.


                                               150
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print),
ISSN 0976 – 6359(Online), Volume 5, Issue 4, April (2014), pp. 147-152 © IAEME

        In single machine experiment adjusted R-square= 87.6 % in comparison to R-suaqre= 98.2%,
which shows a difference of 10.6%. But in case of duplex machining experiment adjusted R-square
is = 97.7 %, in comparison to R-square= 99.7%, which shows a difference of only 2 %.
        So we can conclude that duplex machining process gives more better and consistent outcome
as comparison to single machining process.
        From the following interaction diagrams it is also clear that duplex machining reduces
(almost removed) the interaction between Feed and Speed IVs, as comparison to single machining
process.(A parallel graph shows no interaction between variables)




                                              151
International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print),
ISSN 0976 – 6359(Online), Volume 5, Issue 4, April (2014), pp. 147-152 © IAEME

REFERENCES

 (1)    Lin W.S. “The study of high speed fine turning of austenitic stainless steel”, Journal of
        Achievements in Materials and Manufacturing Engineering, vol-27(2008).
 (2)    Sze-Wei Gan, Han-Seok Lim, Rahman M., Watt Frank “A fine tool servo system for global
        position error compensation for a miniature ultra-precision lathe”, International Journal of
        Machine Tools & Manufacture 47 (2007) 1302–1310.
 (3)    Kumar Vikram, R. CH and Ramamoorthy, B., “Performance of coated tools during hard
        turning under minimum fluid application” Journal of Materials Processing Technology 185
        (2007) 210–216.
 (4)    Sarma, D.K and Dixit, U.S, “A comparison of dry and air-cooled turning of grey cast iron
        with mixed oxide ceramic tool”, Journal of Materials Processing Technology 190 (2007)
        160–172. International Journal of Scientific & Engineering Research Volume 3, Issue 8,
        August-2012 16 ISSN 2229-5518 IJSER © 2012 http ://www.ijser.org.
 (5)    Hasan and Nalbant, Muammer, “The effects of cutting tool geometry and processing
        parameters on the surface roughness of AISI 1030 steel” Gokkaya, Materials and Design 28
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 (6)    Isik,Yahya, “Investigating the machinability of tool steels in turning operations”, Materials
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 (7)    Dhar, N.R. and Ahmed, M.T. and Islam, S. “An experimental investigation on effect of
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        Machine Tools & Manufacture 47 (2007) 748–753.
 (8)    Chang, Chih-Wei and Kuo, Chun-Pao, “Evaluation of surface roughness in laser-assisted
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 (9)    Yadav, Manish kumar and Sinha, Dr.P.K. and Sinha, Dr. Gopal P. “Development of
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 (10)   Yadav, Manish kumar and Sinha, Dr.P.K. and Sinha, Dr. Gopal P. “A comparative study of
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 (11)   Montgomery, Douglas C..; “Design of Experiments”, published by John Wiley and Sons
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 (13)   A. Hemantha Kumar, Krishnaiah.G and V.Diwakar Reddy, “Ann Based Prediction of Surface
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 (14)   Ajeet Kumar Rai, Richa Dubey, Shalini Yadav and Vivek Sachan, “Turning Parameters
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