Skip to main content
Log in

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

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Kurt M, Kaynak Y, Kamber OS, Mutlu B, Bakir B, Koklu U (2010) Influence of molding conditions on the shrinkage and roundness of injection molded parts. Int J Adv Manuf Technol 46:571–578

    Article  Google Scholar 

  2. Park K (2004) A study on flow simulation and deformation analysis for injection-molded plastic parts using three-dimensional solid element. Polym-Plast Technol Eng 43:1569–1585

    Article  Google Scholar 

  3. Li H, Guo Z, Li D (2007) Reducing the effects of weldlines on appearance of plastic products by Taguchi experimental method. Int J Adv Manuf Technol 32:927–931

    Article  Google Scholar 

  4. Shieh JY, Wang LK, Ke SY (2010) A feasible injection molding technique for the manufacturing of large diameter aspheric plastic lenses. Opt Rev 17:399–403

    Article  Google Scholar 

  5. Lu X, Khim LS (2001) A statistical experimental study of the injection molding of optical lens. J Mater Process Technol 113:189–195

    Article  Google Scholar 

  6. Young WB (2005) Effect of process parameters on injection compression molding of pickup lens. Appl Math Model 29:955–971

    Article  MATH  Google Scholar 

  7. Wang PJ, Lai HE (2007) Study of residual birefringence in injection molded lenses. SPE ANTEC Conf Proc, No. 2498

  8. Taguchi G, Chowdhury S, Wu Y (2005) Taguchi’s quality engineering handbook. Wiley, Hoboken

    MATH  Google Scholar 

  9. Montgomery DC (2001) Design and analysis of experiments, 3rd edn. Wiley, New York

    Google Scholar 

  10. Peace GS (1993) Taguchi methods. Addison-Wesley, Taipei

    Google Scholar 

  11. Ozcelik B, Erzurumlu T (2006) Comparison of the warpage optimization in the plastic injection molding using ANOVA, neural network model and genetic algorithm. J Mater Process Technol 171:437–445

    Article  Google Scholar 

  12. Tang SH, Tan YJ, Sapuan SM, Sulaiman S, Ismail N, Samin R (2007) The use of Taguchi method in the design of plastic injection mould for reducing warpage. J Mater Process Technol 182:418–426

    Article  Google Scholar 

  13. Tsai KM (2010) Effect of injection molding process parameters on optical properties of lenses. Appl Opt 49:6149–6159

    Article  Google Scholar 

  14. Altan M (2010) Reducing shrinkage in injection moldings via the Taguchi, ANOVA and neural network methods. Mater Des 31:599–604

    Article  Google Scholar 

  15. Postawa P, Koszkul J (2005) Change in injection moulded parts shrinkage and weight as a function of processing conditions. J Mater Process Technol 162–163:109–115

    Article  Google Scholar 

  16. Ozcelik B, Erzurumlu T (2006) Minimization of warpage and sink index in injection-molded thermoplastic parts using Taguchi optimization method. Mater Des 27:853–861

    Article  Google Scholar 

  17. Deng CS, Chin JH (2005) Hole roundness in deep-hole drilling as analysed by Taguchi methods. Int J Adv Manuf Technol 25:420–426

    Article  Google Scholar 

  18. Shiou FJ, Chen CCA, Li WT (2006) Automated surface finishing of plastic injection mold steel with spherical grinding and ball burnishing processes. Int J Adv Manuf Technol 28:61–66

    Article  Google Scholar 

  19. Mahapatra SS, Patnaik A (2007) Optimization of wire electrical discharge machining (WEDM) process parameters using Taguchi method. Int J Adv Manuf Technol 34:911–925

    Article  Google Scholar 

  20. Yang C, Hung SW (2004) Optimizing the thermoforming process of polymeric foams: an approach by using the Taguchi method and the utility concept. Int J Adv Manuf Technol 24:353–360

    Article  Google Scholar 

  21. Li B, Nye TJ, Metzger DR (2006) Multi-objective optimization of forming parameters for tube hydroforming process based on the Taguchi method. Int J Adv Manuf Technol 28:23–30

    Article  Google Scholar 

  22. Mok SL, Kwong CK, Lau WS (1999) Review of research in the determination of process parameters for plastic injection molding. Adv Polym Technol 18:225–236

    Article  Google Scholar 

  23. Chen Z, Turng LS (2005) A review of current developments in process and quality control for injection molding. Adv Polym Technol 24:165–182

    Article  Google Scholar 

  24. Myers RH, Montgomery DC (2002) Response surface methodology: process and product optimization using designed experiments, 2nd edn. Wiley, New York

    Google Scholar 

  25. Moore LJ, Sa P (1999) Comparisons with the best in response surface methodology. Stat Probl Lett 44:189–194

    Article  MathSciNet  MATH  Google Scholar 

  26. Bas D, Boyaci IH (2007) Modeling and optimization I: usability of response surface methodology. J Food Eng 78:836–845

    Article  Google Scholar 

  27. Lizotte DJ, Greiner R, Schuurmans D (2012) An experimental methodology for response surface optimization methods. J Glob Optim 53:699–736

    Article  MathSciNet  MATH  Google Scholar 

  28. Chiang KT, Chang FP (2007) Analysis of shrinkage and warpage in an injection-molded part with a thin shell feature using the response surface methodology. Int J Adv Manuf Technol 35:468–479

    Article  Google Scholar 

  29. Andrisano AO, Gherardini F, Leali F, Pellicciari M, Vergnano A (2011) Design of simulation experiments method for injection molding process optimization. Int conf Innov Meth Prod Des, Venice, Italy

  30. Wang G, Zhao G, Li H, Guan Y (2011) Research on optimization design of the heating/cooling channels for rapid heat cycle molding based on response surface methodology and constrained particle swarm optimization. Expert Syst Appl 38:6705–6719

    Article  Google Scholar 

  31. Wua L, Yick KL, Ng SP, Yip J, Kong KH (2012) Parametric design and process parameter optimization for bra cup molding via response surface methodology. Expert Syst Appl 39:162–171

    Article  Google Scholar 

  32. Kwak JS (2005) Application of Taguchi and response surface methodologies for geometric error in surface grinding process. Int J Mach Tools Manuf 45:327–334

    Article  Google Scholar 

  33. Kurtaran H, Erzurumlu T (2006) Efficient warpage optimization of thin shell plastics parts using response surface methodology and genetic algorithm. Int J Adv Manuf Technol 27:468–472

    Article  Google Scholar 

  34. Kilickap E (2010) Modeling and optimization of burr height in drilling of Al-7075 using Taguchi method and response surface methodology. Int J Adv Manuf Technol 49:911–923

    Article  Google Scholar 

  35. Tsao CC (2012) Evaluation of the drilling-induced delamination of compound core-special drills using response surface methodology based on the Taguchi method. Int J Adv Manuf Technol 62:241–247

    Article  Google Scholar 

  36. Brient A, Brissot M, Rouxel T, Sangleboeuf JC (2011) Influence of grinding parameters on glass workpieces surface finish using response surface methodology. J Manuf Sci Eng 133. doi:10.1115/1.4004317

  37. Pradhan MK (2013) Estimating the effect of process parameters on surface integrity of EDMed AISI D2 tool steel by response surface methodology coupled with grey relational analysis. Int J Adv Manuf Technol 67:2051–2062

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kuo-Ming Tsai.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tsai, KM., Tang, BH. Determination of injection molding process window based on form accuracy of lens using response surface methodology. Int J Adv Manuf Technol 75, 947–958 (2014). https://doi.org/10.1007/s00170-014-6185-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-014-6185-9

Keywords

Navigation