Determination of injection molding process window based on form accuracy of lens using response surface methodology

The purpose of this study is to establish a process window of injection molding process for the optimal form accuracy of spherical lenses. First, the significant factors influencing lens form accuracy are identified by Taguchi parameter design. These key factors are used to perform full factorial experiments and to establish the response surface model. Next, the concave response surface of form accuracy is obtained by Central Composite Design via sequential searching. The curve fitting is then used to obtain the injection molding process window for given spherical lens form accuracy. As a result, the injection molding process window is elliptical, the best form accuracy is 0.3758 μm at the elliptical center when the mold temperature is 85 °C, the cooling time is 9.6 s, and the packing time is 1.9 s. The average error is 7.92 % based on experimental verifications for three mold temperatures. In addition, a lens with a form accuracy of 0.5 μm is taken as an example to validate the injection molding process window. The results show that the average error between the experimental data and the prediction values is 10.58 %. Therefore, the proposed method for constructing a process window is reasonably accurate.

[1]  Erol Kilickap,et al.  Modeling and optimization of burr height in drilling of Al-7075 using Taguchi method and response surface methodology , 2010 .

[2]  Mohan Kumar Pradhan,et al.  Estimating the effect of process parameters on surface integrity of EDMed AISI D2 tool steel by response surface methodology coupled with grey relational analysis , 2013 .

[3]  Genichi Taguchi,et al.  Taguchi's Quality Engineering Handbook , 2004 .

[4]  Kuo-Ming Tsai.  Effect of injection molding process parameters on optical properties of lenses , 2010 .

[5]  Mirigul Altan,et al.  Reducing shrinkage in injection moldings via the Taguchi, ANOVA and neural network methods , 2010 .

[6]  Bing Li,et al.  Multi-objective optimization of forming parameters for tube hydroforming process based on the Taguchi method , 2006 .

[7]  P. Postawa,et al.  Change in injection moulded parts shrinkage and weight as a function of processing conditions , 2005 .

[8]  Joanne Yip,et al.  Parametric design and process parameter optimization for bra cup molding via response surface methodology , 2012, Expert Syst. Appl..

[9]  Chyn-Shu Deng,et al.  Hole roundness in deep-hole drilling as analysed by Taguchi methods , 2005 .

[10]  Babur Ozcelik,et al.  Minimization of warpage and sink index in injection-molded thermoplastic parts using Taguchi optimization method , 2006 .

[11]  B. Ozcelik,et al.  Experimental and numerical studies on the determination of twist drill temperature in dry drilling: A new approach , 2006 .

[12]  Babur Ozcelik,et al.  Comparison of the warpage optimization in the plastic injection molding using ANOVA, neural network model and genetic algorithm , 2006 .

[13]  Keun Park,et al.  A Study on Flow Simulation and Deformation Analysis for Injection-Molded Plastic Parts Using Three-Dimensional Solid Elements , 2005 .

[14]  Hasan Kurtaran,et al.  Efficient warpage optimization of thin shell plastic parts using response surface methodology and genetic algorithm , 2006 .

[15]  L. Turng,et al.  A review of current developments in process and quality control for injection molding , 2005 .

[16]  Deniz Baş,et al.  Modeling and optimization I: Usability of response surface methodology , 2007 .

[17]  Guoqun Zhao,et al.  Research on optimization design of the heating/cooling channels for rapid heat cycle molding based on response surface methodology and constrained particle swarm optimization , 2011, Expert Syst. Appl..

[18]  F. Leali,et al.  Design Of Simulation Experiments method for Injection Molding process optimization , 2011 .

[19]  Yusuf Kaynak,et al.  Influence of molding conditions on the shrinkage and roundness of injection molded parts , 2010 .

[20]  Chao-Chang A. Chen,et al.  Automated surface finishing of plastic injection mold steel with spherical grinding and ball burnishing processes , 2006 .

[21]  C. C. Tsao,et al.  Evaluation of the drilling-induced delamination of compound core-special drills using response surface methodology based on the Taguchi method , 2012 .

[22]  Amar Patnaik,et al.  Optimization of wire electrical discharge machining (WEDM) process parameters using Taguchi method , 2007 .

[23]  C. Kwong,et al.  Review of research in the determination of process parameters for plastic injection molding , 1999 .

[24]  N. Ismail,et al.  The use of Taguchi method in the design of plastic injection mould for reducing warpage , 2007 .

[25]  Xuehong Lu,et al.  A statistical experimental study of the injection molding of optical lenses , 2001 .

[26]  Douglas C. Montgomery,et al.  Response Surface Methodology: Process and Product Optimization Using Designed Experiments , 1995 .

[27]  Hongsheng Li,et al.  Reducing the effects of weldlines on appearance of plastic products by Taguchi experimental method , 2007 .

[28]  Ko-Ta Chiang,et al.  Analysis of shrinkage and warpage in an injection-molded part with a thin shell feature using the response surface methodology , 2007 .

[29]  D. Lizotte,et al.  An experimental methodology for response surface optimization methods , 2012, J. Glob. Optim..

[30]  Jae-Seob Kwak,et al.  Application of Taguchi and response surface methodologies for geometric error in surface grinding process , 2005 .

[31]  Linda J. Moore,et al.  Comparisons with the best in response surface methodology , 1999 .

[32]  C. J. Yang,et al.  Optimising the thermoforming process of polymeric foams: an approach by using the Taguchi method and the utility concept , 2004 .

[33]  Wen-Bin Young,et al.  Effect of process parameters on injection compression molding of pickup lens , 2005 .

[34]  T. Rouxel,et al.  Influence of Grinding Parameters on Glass Workpieces Surface Finish Using Response Surface Methodology , 2011 .