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					International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
INTERNATIONAL JOURNAL OF MECHANICAL ENGINEERING
6340(Print), ISSN 0976 – 6359(Online) Volume 5, Issue 1, January (2014), © IAEME
                               AND TECHNOLOGY (IJMET)

ISSN 0976 – 6340 (Print)
ISSN 0976 – 6359 (Online)                                                        IJMET
Volume 5, Issue 1, January (2014), pp. 108-115
© IAEME: www.iaeme.com/ijmet.asp
Journal Impact Factor (2013): 5.7731 (Calculated by GISI)                   ©IAEME
www.jifactor.com




    OPTIMIZATION OF CRITICAL PROCESSING PARAMETERS FOR
 PLASTIC INJECTION MOLDING OF POLYPROPYLENE FOR ENHANCED
      PRODUCTIVITY AND REDUCED TIME FOR NEW PRODUCT
                       DEVELOPMENT

                                Mr. A.B. Humbe(1),    Dr. M.S. Kadam(2)
                (1)
                      Student, M.E. Manufacturing, Mechanical Engineering Department,
                                    J.N.E.C. Aurangabad, Maharashtra, India
                              (2)
                                  Professor, Mechanical Engineering Department,
                                    J.N.E.C. Aurangabad, Maharashtra, India




ABSTRACT

       Injection molding has been a challenging process for many plastic components manufacturers
and researchers to produce plastics products meeting the requirements at very economical cost. Since
there is global competition in injection molding industry, sousing trial and error approach to
determine process parameters for injection molding is no longer hold good enough. Since plastic is
widely used polymer due to its high production rate, low cost and capability to produce intricate
parts with high precision. It is much difficult to set optimal process parameter levels which may
cause defects in articles, such as shrinkage, war page, line defects. Determining optimal process
parameter setting critically influences productivity, quality and cost of production in plastic injection
molding (PIM) industry. In this paper optimal injection molding condition for minimum cycle time
were determined by the DOE technique of Taguchi methods. The various observation has been taken
for material namely Polypropylene (PP).The determination of optimal process parameters were based
on S/N ratios.

Keywords: Injection Molding, DOE, Taguchi Optimization.

PROCEDURE

  • Set the parameters based on historical data and experience
  • Fine tune the process parameters for the component which can be considered for evaluation and
    observe the trend while setting each process.
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International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online) Volume 5, Issue 1, January (2014), © IAEME

 •       Document the data for research and analysis further using DOE (Taguchi Method/ Minitab)
 •       Derive a standard based on the material and the configuration
 •       Optimize the setting time and validate the process Injection Molding Machine Sectional view
 •       Document the data for research and analysis further using DOE (Taguchi Method/Minitab)
 •       Derive a standard based chart on the material and the configuration.

EXPERIMENTATION

        In the analysis part we have analyzed 4 important parameters like Melting Temperature,
Holding Pressure, Cool Time and Injection pressure at three levels, The response for this considered
is cycle time.

                     Table No.1 Large Component
 SR. PART NAME/ MT IP(MPa) HP(MPa) COOL         CYCLE                           PSNRA1      PMEAN1
 NO. PARAMETERS (°c)                    TIME     TIME
                                        (sec)    (Sec)

                              225      81         55         20         39      -31.8213       39
                              225      84         52         22         38      -31.5957       38
           Large              225      85         56         23         42       -32.465       42
           component          228      81         52         23         40      -32.0412       40
     1                        228      84         56         20         39      -31.8213       39
           with size: 525
           X 320 X 80mm       228      85         55         22         42       -32.465       42
                              229      81         56         22         44      -32.8691       44
                              229      84         55         23         48      -33.6248       48
                              229      85         52         20         42       -32.465       42
                              219      76         50         26         35      -30.8814       35
                              219      71         48         25         34      -30.6296       34
           Large              219      79         51         22         35      -30.8814       35
           component          220      76         48         22         36      -31.1261       36
     2     with size: 600     220      71         51         26         39      -31.8213       39
           X 200 X
                              220      79         50         25         39      -31.8213       39
           195mm
                              225      76         51         25         41      -32.2557       41
                              225      71         50         22         34      -30.6296       34
                              225      79         48         26         40      -32.0412       40
                              204      44         25         16         66      -36.3909       66
                              204      50         30         23         67      -36.5215       67
           Size of Large      204      56         33         27         69       -36.777       69
           component is:      205      44         30         27         69       -36.777       69
     3                        205      50         33         16         70       -36.902       70
           500 X 275 X
           175mm              205      56         25         23         77      -37.7298       77
                              217      44         33         23         78      -37.8419       78
                              217      50         25         27         79      -37.9525       79
                              217      56         30         16         79      -37.9525       79




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International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online) Volume 5, Issue 1, January (2014), © IAEME

Analysis of the S/N Ratio
SN ratio (Smaller is Better)




            PATRT-1                              PART-2                         PART-3


Part -1:-The main effect plot for SN ratio graphs above depicts certain characteristics of each
parameter. The Melting Temperature graph indicates the steep slope when compared to other
parameter graph curves. This also means that it is holding the first rank in control parameters among
the chosen ones. The Melting Temperature curve slope starts very shallow slope from 225 to 228 and
after that its slope is very steep till 229. The slope of this graph is very steep, which means that we
need to attack or act on this parameter first to reduce our cycle time.

Part -2:-The main effect plot for SN ratio graphs above depicts certain characteristics of each
parameter. The Melting Temperature graph indicates the steep slope when compared to other
parameter graph curves. This also means that it is holding the first rank in control parameters among
the chosen ones. The Melting Temperature curve slope starts very steep slope from 219 to 220 and
after that its slope is very flat till 225. This means that the best temperature to work upon is around
220 and not above that, as the slope becomes flat, there is no much effect on cycle time. The slope of
this graph is very steep, which means that we need to attack or act on this parameter first to reduce
our cycle time. The Cool Time graph is also equally steep in nature so the second closest ranking is
this and so we need to attack this after Melt temperature. This graph also depicts that the slope of
curve is very flat after 25 sec. So our best cycle time would be achieved below 25 sec.

Part -3:-The main effect plot for SN ratio graphs above depict certain characteristics of each
parameter. The Melting Temperature graph indicates the very steep slope when compared to other
parameter graph curves.. The Melting Temperature curve slope starts very steep slope from 204 to
205 and after that also its slope is very steep till 217. This means that the best temperature to work
upon is around or above 217 and not below that, as the slope continues further, as there will be much
effect on cycle time. The slope of this graph is very steep, which means that we need to attack or act
on this parameter first to reduce our cycle time.




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International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online) Volume 5, Issue 1, January (2014), © IAEME

                                 Table No.2 Small Component
   SR. PART NAME/         MT     IP(MPa)   HP(MPa)   COOL     CYCLE    PSNRA1     PMEAN1
   NO. PARAMETERS         (°c)                       TIME      TIME
                                                      (sec)    (Sec)


                          201      58        24       15        23     -27.2346     23
                          201      56        20       19        26     -28.2995     26
        Size of Small     201      60        19       14        25     -27.9588     25
    4   component is:     199      58        20       14        26     -28.2995     26
        80 X 50 X 45      199      56        19       15        27     -28.6273     27
        mm                199      60        24       19        28     -28.9432     28
                          204      58        19       19        27     -28.6273     27
                          204      56        24       14        21     -26.4444     21
                          204      60        20       15        24     -27.6042     24
                          200      49        21       21        29      -29.248     29
                          200      56        20       18        31     -29.8272     31
        Size of Small     200      51        19       22        34     -30.6296     34
    5   component is:     196      49        20       22        33     -30.3703     33
        70 X 35 X 25      196      56        19       21        37      -31.364     37
        mm                196      51        21       18        40     -32.0412     40
                          207      49        19       18        39     -31.8213     39
                          207      56        21       22        37      -31.364     37
                          207      51        20       21        33     -30.3703     33
                          196      45        30       14        24     -27.6042     24
                          196      40        28       20        31     -29.8272     31
        Size of Small     196      47        35       12        33     -30.3703     33
        component is:     192      45        28       12        36     -31.1261     36
    6
        35 X 35 X 15      192      40        35       14        38     -31.5957     38
        mm                192      47        30       20        31     -29.8272     31
                          198      45        35       20        37     -31.3840     37
                          198      40        30       12        32     -30.1030     32
                          198      47        28       14        39     -31.8213     39

Analysis of the S/N Ratio
SN ratio (Smaller is Better)




          PATRT-4                           PART-5                       PART-6

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International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online) Volume 5, Issue 1, January (2014), © IAEME

Part -4:-The main effect plot for SN ratio graphs above depict certain characteristics of each
parameter. The Melting Temperature graph indicates the steep slope when compared to other
parameter graph curves. This also means that it is holding the first rank in control parameters among
the chosen ones. The Melting Temperature curve slope starts very steep slope from 199 to 201 and
after that its slope is little flat till 204. This means that the best temperature to work upon is around
201 and not above that, as the slope becomes little flat, there is no much effect on cycle time. The
slope of this graph is very steep, which means that we need to attack or act on this parameter first to
reduce our cycle time. The Hold Pressure is also very steep from 19 till 24. So this parameter also
play important role as second player.
        The Cool Time graph is also equally steep in nature so the third closest ranking is this and so
we need to attack this after Melt temperature. This graph also depicts that the slope of curve is less
steep till 15 sec, after that the steep increases till 19. So our best cycle time would be achieved
around 19 sec.

Part -5:-The main effect plot for SN ratio graphs above depicts certain characteristics of each
parameter. The Melting Temperature graph indicates the steep slope when compared to other
parameter graph curves. This also means that it is holding the first rank in control parameters among
the chosen ones. The Melting Temperature curve slope starts very steep slope from 196 to 200 and
after that its slope is changing direction till 207. This means that the best temperature to work upon is
around 200 and not above or below that, as the slope changes direction, and there is no much effect
on cycle time. The slope of this graph is very steep, which means that we need to attack or act on this
parameter first to reduce our cycle time.
        The Hold Pressure is also very steep from 19 till 20 and after that it is changing its direction
of slope till 21. So this parameter also play important role as second player. The best cycle time will
be achieved if this parameter is kept around 20.
        The Cool Time graph is also equally steep in nature so the third closest ranking is this and so
we need to attack this after Melt temperature. This graph also depicts that the slope of curve is
changing at 21. So our best cycle time would be achieved around 21 sec.

Part 6:-The main effect plot for SN ratio graphs above depict certain characteristics of each
parameter. The Hold Pressure graph indicates the steep slope when compared to other parameter
graph curves. This also means that it is holding the first rank in control parameters among the chosen
ones. The Melting Temperature curve slope starts very steep slope from 28 to 30 and after that its
slope is changing direction till 35. This means that the best pressure to work upon is around 30 and
not above or below that, as the slope changes direction, and there is no much effect on cycle time.
The slope of this graph is very steep, which means that we need to attack or act on this parameter
first to reduce our cycle time.
         The Melting Temperature is also very steep from 192 till 196 and after that it is changing its
direction of slope till 198. So this parameter also play important role as second player. The best cycle
time will be achieved if this parameter is kept around 196.
The Cool Time and Injection pressure graph does not play a major role in the Cycle time.

CONCLUSION

        Taguchi method stresses the importance of studying the response variation using the signal-
to-noise (S/N) ratio, resulting in minimization of quality characteristics variation due to
uncontrollable parameter. The procurement process was considered as the quality characteristics with
the objective of minimizing the Costs involved in the process of procurement.


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International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online) Volume 5, Issue 1, January (2014), © IAEME

        3 different experimentations carried out to study the interaction of each parameter on the
other. Many times it becomes very difficult to separate out the contribution of each factor as whole
on to the final response. The 3 experiments conducted were for Large size components. Out of the 3
components, all the components exhibit same with respect to its top ranking parameter, that is Melt
Temperature. It is can unanimously said that in large size parts the Melt temperature play in
important role in deciding the cycle time. There is no pattern seen in other parameters behavior in the
experimentation The 3 experiments conducted for small size components reveal a varied ranking. For
2 parts Melt temp was important and last part it was not. When we closed analyzed the reason for
such behavior and found out the complexity of part, in term of intricate shape, fine features was
driving this change.
        Design of Experiments is a statistical method and Taguchi method is very proven and robust
so we have used this technique. It is important to remember that statistical methods are based on
assumptions and iterations, which means the results obtained are to some percentage level of
confidence and not 100%. Taguchi claims that his technique is 90% confident on the results.
Also, once we act upon / attach on one parameter of any experimentation, we need to run DOE to see
the results and find out the ranking of the parameter again. Because when the readings / observations
change, the ranking may change depending on its portion of influence on the response parameter. If
the ranking remains same, you can carry out next set of experiments by only changing the parameter
ranked first. If the ranking changes then our experimentation should attached the next parameter
which is ranked. So like this, we can continue to go on, till we receive a satisfactory level of
outcome.
        DOE also gives use some empirical relationships in the form of equation that can be used as a
quick reference or guideline while we need to take major decisions like deciding cycle time quickly
when a new customer is asking for basic quotation OR while making major decision like buying of
additional Injection molding machine, which costs in cores of rupees, etc.
        We had carried out 3 large and 3 small components experimentations with different
parameters. Out of the 9 runs per component, we have chosen the top 2 best SN ratio values from
each Large size components and small size component and carried out a regression analysis.
        With the available parameters, we have a regression equation for all the 6 experiments. By
properly substituting the values of the parameters, we can take decisions for future projects.




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International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online) Volume 5, Issue 1, January (2014), © IAEME

REFERENCE CHART

                     Material                   MT (°c)    IP( MPa)      HP(MPa) CT(sec)
      Polypropylene(PP)
      Large Sized                                 209          52           30          23
      Volume range-600cm cube to 1200
      cm cube
      Polypropylene(PP)
      Small Sized                                 202          54           19          20
      Volume range-up to 650cm cube


       The reference chart standardized with the values for the process variables will be validated
for the upcoming automotive components that are awaiting pilot run of production. The process
would be repeated for the variants to ensure consistency in the physical characteristics of the
component produced. Validation will be carried out by bring out actual development of two
components. Trials and testing would address the phase of validation as the mould would be tried out
for checking the nature of the physical components as an outcome of the development process. The
study has evolved reference values for the significant factors suitable for each category of the
material. Following is the compilation for the conclusions drawn.

Material : PP – Small
For small Polypropylene parts, cycle time increased with increase in cooling time & also PP melt
temperature Coolant flow & temperature could be controlled to reduce cycle time. It was observed
that PP melt temperature in the range of 200-206 degcel. & cooling time of 19 to 21 sec produced
consistent parts with optimum cycle time.

Material : PP Large
For large Polypropylene parts, cycle time increased with increase in cooling time & also PP melt
temperature. It was observed that PP melt temperature in the range of 203-209 degcel. & cooling
time of 23 to 25 sec produced consistent parts with optimum cycle time.

REFERENCES

 1.   Optimization of Weld Line Quality in Injection Molding Using an Experimental Design
      Approach Tao c. Chang andErnest Faison, Journal of Injection Moulding Technology, JUNE
      1999, Vol. 3, No. 2 PP 61-66.
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      Optimization: A Case Study Velia Garc´ıaLoera, José M. Castro, Jesus Mireles Diaz, O´ scar
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      Equipment Based On Orthogonal Experiment And Analysis Yanwei1 Huyong IEEE 2011
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      Journal of Engineering & Technology IJET-IJENS Vol: 11 No: 01 PP 182-187.



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International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 –
6340(Print), ISSN 0976 – 6359(Online) Volume 5, Issue 1, January (2014), © IAEME

 5.    Optimization of Plastics Injection Molding Processing Parameters Based on the Minimization
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