1. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print),
ISSN 0976 – 6359(Online), Volume 5, Issue 4, April (2014), pp. 103-109 © IAEME
103
EFFECT OF PROCESS PARAMETERS ON FLATNESS OF PLASTIC
COMPONENT
Lakshmana Naik T K1
, Veerabhadrappa Algur2
, Dr. A Thimmana Gouda3
,
Ravi B Chikmeti4*
, Praveena K V, Shivraj R, Shamanth H R, Ramzan S P5
1
Assistant Professor, Mechanical Engineering Department, RYMCE, Bellary, Karnataka.
2
Assistant Professor, Industrial Production Engineering, RYMCE, Bellary, Karnataka.
3
Professsor & Head, Industrial Production Engineering, RYMCE, Bellary, Karnataka.
4*
M.Tech. (Production Engineering), Mechanical Engineering Department, PDA CE,
Gulbarga, Karnataka
5
BE( Students), Industrial Production Engineering, RYMCE, Bellary, Karnataka
ABSTRACT
Dimensional changes because of shrinkage is one of the most important problem in
production of plastic parts using plastic injection molding(PIM). In this study, effect of injection
molding parameters on surface flatness of plastic component is investigated and achieving the
flatness according to customer requirement is the big task, for that this work is carried out.
Process parameters like nozzle temperature, injection pressure, holding pressure release and
cooling time are selected in this work. By optimization technique, determined optimum process
parameters are the nozzle temperature 300 °C, injection pressure 35 bar, holding pressure release
5 Sec. and cooling time 54 Sec.
Keywords: Plastic Injection Molding, Surface Flatness, Taguchi Technique etc.
1. INTRODUCTION
Nowadays, competitive market requires producers to produce high quality parts, with lower
price in the least possible time. Injection molding is known as an effective process for mass
production of plastic parts with complicated forms and high dimensional precision. In this method,
high pressure fluid polymer is injected to the cavity with desired form. Next, under high pressure,
fluid solidifies. During the process, plastic materials are under high pressure and temperature.
INTERNATIONAL JOURNAL OF MECHANICAL ENGINEERING
AND TECHNOLOGY (IJMET)
ISSN 0976 – 6340 (Print)
ISSN 0976 – 6359 (Online)
Volume 5, Issue 4, April (2014), pp. 103-109
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2. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print),
ISSN 0976 – 6359(Online), Volume 5, Issue 4, April (2014), pp. 103-109 © IAEME
104
Materials are cooled to get desired form. Injection molding process can be divided into four stages:
Plasticization, injection, packing and cooling. Although molding process may seem simple, the
molded polymers are affected by many machine parameters and process condition.
Incorrect input parameters settings will cause bad quality of surface roughness, decreases
dimensional precision, Warpage, unacceptable wastes, increases lead time and cost .Therefore,
finding the optimized parameters is highly desirable. In past scientists used trials and error to find
good process conditions but this method is time and cost consuming [1].The Taguchi method is a
traditional approach for robust experimental design that seeks to obtain the best combination of
factor/level for the lowest societal cost while fulfilling customers’ requirements. Over the past
decade the Taguchi method has been widely applied to optimize the parameter design problems,
which uses orthogonal array (OA) to arrange the experiments and employs signal-to-noise ratio
(SNR) to evaluate the performance of the response of each experimental run. Nevertheless, Taguchi’s
method can only be used to resolve an optimal single response problem; it cannot be used to
simultaneously optimize the multi response problem. Unfortunately, in the real world, most
customers consider more than one quality response problem, while selecting industrial products. In
addition, the goals of the multi responses often conflict with each other [2].
Figure 1: Molding process
1.1 Problem statement
Maintaining a surface flatness in plastic injection molding is big task.
1.2 Objective
Study the effect of process parameters on flatness of plastic component
2.0 DESIGN OF EXPERIMENT
The DOE procedure consists of the following four steps:
Planning: Definition of the problem and the objective, and development of an experimental plan.
Screening: Reduction of the number of variables by identifying the key variables that affect product
quality.
Optimization: Determination of the optimal values for various experimental factors.

3. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print),
ISSN 0976 – 6359(Online), Volume 5, Issue 4, April (2014), pp. 103-109 © IAEME
105
Verification: performing a follow-up experiment at the predicted best processing conditions to
confirm the Optimization, results. In this study, parameter design is coupled to achieve the optimum
levels of process Parameters leading to minimum shrinkage during the manufacturing of plastic parts.
2.1 Steps in Taguchi Parameter Design
In this study, Taguchi parameter design was used for identifying the significant processing
parameters and Produced required surface flatness of plastic component [3].
Figure 2: Steps of Taguchi parameter design
3.0 EXPERIMENTAL STUDIES
The experimental plan was formulated considering four parameters and three levels based on
the Taguchi technique. Nozzle temperature (A), injection pressure (B), holding pressure release (C)
and cooling time, these are process parameters is considered for the study. Process parameters setting
with the highest S/N ratio always yield the optimum quality with minimum variance [4]. The levels
of these variables chosen for experimentation are given in the Table 1.
In the present investigation an L9 orthogonal array was chosen as shown in Table 2. The
selected of the orthogonal array is based on the condition that the degrees of freedom for the
orthogonal array should be greater than, or equal to, the sum of the variables. The experiments were
conducted based on the run order generated by Taguchi model and the results were obtained. This
analysis includes the rank based on the delta statistics, which compares the relative value of the
effects. S/N ratio is a response which consolidates repetitions and the effect of noise levels into one
data point. The experimental results were transformed into signal-to-noise ratio (S/N) ratios. An S/N
ratio is defined as the ratio of the mean of the signal to the standard deviation of the noise. The S/N
ratio indicates the degree of the predictable performance of a product or process in the presence of
noise factors. The S/N ratio for the surface flatness using ‘smaller the better’ characteristics, which
can be calculated as logarithmic transformation of the loss function is given as
S/N = -10 log10 (MSD) ------------ (1)
Where MSD = Mean Square Deviation
For the smaller the better characteristic,
MSD = (Y1
2
+ Y2
2
+ Y3
2
+ ………) x 1/ n
Where Y1, Y2, Y3 are the responses and ‘n’ is the number of tests in a trial.

4. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print),
ISSN 0976 – 6359(Online), Volume 5, Issue 4, April (2014), pp. 103-109 © IAEME
106
3.1 Experimental design
Table 1: Selected Factors and Levels (L1, L2, L3, L4)
SI.
NO. Factors L1 L2 L3 L4
1 Nozzle Temperature, A (˚C) 240 280 300 240
2 Injection pressure, B (bar) 15 25 35 15
3 Holding pressure release, C (bar) 5 10 15 5
5 Cooling time, D (sec.) 27 54 81 27
Table 2: L9 OA
(OA)
SI No. A B C D
1 1 1 1 1
2 1 2 2 2
3 1 3 3 3
4 2 1 2 3
5 2 2 3 1
6 2 3 1 2
7 3 1 3 2
8 3 2 1 3
9 3 3 2 1
Table 3: Combination of parameters in (L9) Orthogonal Array
Process Parameters
SI No. A B C D
1 240 15 5 27
2 240 25 10 54
3 240 35 15 81
4 280 15 10 81
5 280 25 15 27
6 280 35 5 54
7 300 15 15 54
8 300 25 5 81
9 300 35 10 27
4.0 RESULTS AND DISCUSSIONS
Experimental values of surface flatness and the calculated values of signal to noise ratio for a
given response using Equation 1, and are listed in table 4. The Taguchi’s technique suggested that the
analysing of signal to noise ratio using conceptual approach that involves graphing the special effects
and visual making out the significant aspects. The rankings of process parameter levels for surface
flatness are shown in Table 5.

5. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print),
ISSN 0976 – 6359(Online), Volume 5, Issue 4, April (2014), pp. 103-109 © IAEME
107
Table 4: Summary of Results
Table 5: Control factors
Figure 3: Measurement of surface flatness
SI No. Process Parameters Response(mm) S/N Ratio
A B C D
1 240 15 5 27 0.2 13.97
2 240 25 10 54 0.16 15.91
3 240 35 15 81 0.12 18.41
4 280 15 10 81 0.1 20
5 280 25 15 27 0.06 24.43
6 280 35 5 54 0.02 33.97
7 300 15 15 54 0.03 30.45
8 300 25 5 81 0.04 27.95
9 300 35 10 27 0.05 26.02
Parameters
levels A B C D
1 16.096 21.473 25.296 21.473
2 26.133 22.763 20.643 26.776
3 28.14 26.133 24.43 22.12
∆ 12.043 4.66 4.653 5.303
Rank 1 3 4 2

6. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print),
ISSN 0976 – 6359(Online), Volume 5, Issue 4, April (2014), pp. 103-109 © IAEME
108
Graph 1: S/N Response vs nozzle temperature Graph 2: S/N Response vs injection pressure
Graph 3: S/N Response vs holding pressure release Graph 4: S/N Response vs cooling time
5. CONCLUSION
Producing quality of plastic components is big task in industry. According requirements, we
produced quality of plastic part by adopting optimization technique and also determined optimum
process parameters are the nozzle temperature 300 °C, injection pressure 35 bar, holding pressure 5
Sec. and Cooling time 54 Sec., by setting these parameters, achieved required surface flatness of
plastic component.

7. International Journal of Mechanical Engineering and Technology (IJMET), ISSN 0976 – 6340(Print),
ISSN 0976 – 6359(Online), Volume 5, Issue 4, April (2014), pp. 103-109 © IAEME
109
Figure 4: Plastic component
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