Your SlideShare is downloading. ×
30120140504013
30120140504013
30120140504013
30120140504013
30120140504013
30120140504013
30120140504013
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

30120140504013

62

Published on

Published in: Technology, Business
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
62
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
2
Comments
0
Likes
0
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide

Transcript

  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 © IAEME: www.iaeme.com/ijmet.asp Journal Impact Factor (2014): 7.5377 (Calculated by GISI) www.jifactor.com IJMET © I A E M E
  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 REFERENCES [1] Alireza Akbarzadeh and Mohammad Sadeghi, Parameter Study in Plastic Injection Molding Processusing Statistical Methods and IWO Algorithm, International Journal of Modeling and Optimization, Vol. 1, No. 2, June 2011 [2] Chih-Hsien Chen1 and Hsu-Hwa Chang2,*, Robust Parameter Design by Neural networks and Genetic Algorithms, The 24th Workshop on Combinatorial Mathematics and Computation Theory. [3] Mr. Ravi B Chikmeti , Prof. Sunil Mangshetty , “A Literature Review on Reducing the Warpage of Plastic Component by using Taguchi Optimization Technique, Gate location and Direction of Polishing on Core and Cavity”, Mechanical Engineering Dept., PDA College of Engineering and Technology, Gulbarga,, Karnataka, India, IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE) ISSN: 2278-1684 Volume 4, Issue 1 (Nov-Dec. 2012), PP 38-42 [4] K Palanikumar, “Application of Taguchi and Response Surface Methodologies for Surface Methodologies for Surface Roughness in Machining Glass Fiber Reinforced by PCD Tooling”, The International Journal of Advanced Manufacturing Technology, vol. 36, No. 1-2, 2008, pp. 19-27. [5] A.B. Humbe and Dr. M.S. Kadam, “Optimization of Critical Processing Parameters for Plastic Injection Molding of Polypropylene for Enhanced Productivity and Reduced Time for New Product Development”, International Journal of Mechanical Engineering & Technology (IJMET), Volume 5, Issue 1, 2014, pp. 108 - 115, ISSN Print: 0976 – 6340, ISSN Online: 0976 – 6359. [6] Anandrao B. Humbe and Dr. M.S. Kadam, “Optimization of Critical Processing Parameters for Plastic Injection Molding for Enhanced Productivity and Reduced Time for Development”, International Journal of Mechanical Engineering & Technology (IJMET), Volume 4, Issue 6, 2013, pp. 223 - 226, ISSN Print: 0976 – 6340, ISSN Online: 0976 – 6359.

×