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Influential factors on the outer lens color in an industrial injection molding process

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Abstract

The quality and the aspect of outer lens fabricated by an injection molding process are an essential part for the optical properties of vehicular lighting system. This work is accurately addressed to identify the influential factors on the red color of the outer lens made of blends of polycarbonate and acrylonitrile butadiene styrene, which are mixed with a red masterbatch. Seven factors were investigated in this work: masterbatch concentration, mold and nozzle temperatures, holding and packing pressures, and holding and packing times. The main influential factors were found through a design of experiments in a linear approximation. The outer lens's red color is mainly influenced by the masterbatch concentration, the nozzle temperature, holding time, and the holding pressure, in a decreasing order. In contrast, the mold temperature, packing pressure, and packing time are not statically significant in the color appearance.

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References

  1. McKeen LW (2008) Effect of temperature and other factors on plastics and elastomers 2nd edn. William Andrew, Norwich, pp 1–39, Plastics Design Library

    Book  Google Scholar 

  2. Gordon MJ Jr (2010) Total quality process control for injection molding, 2nd edn. Wiley, New York, pp 169–283

    Book  Google Scholar 

  3. Gruber DP, Berger G, Pacher G, Friesenbichler W (2011) Novel approach to the measurement of the visual perceptibility of sink marks on injection molding parts. Polym Test 30(6):651–656

    Article  Google Scholar 

  4. Farshi B, Gheshmi S, Miandoabchi E (2011) Optimization of injection molding process factors using sequential simplex algorithm. Mater Des 32(1):414–423

    Article  Google Scholar 

  5. Kenig S, Ben-David A, Omer M, Sadeh A (2001) Control of properties in injection molding by neural networks. Eng Appl Artif Intell 14(6):819–823

    Article  Google Scholar 

  6. Rosato DV, Rosato DV, Rosato MV (2004) Injection molding. Elsevier, New York, pp 192–226

    Google Scholar 

  7. Shen C, Wang L, Li Q (2007) Optimization of injection molding process factors using combination of artificial neural network and genetic algorithm method. J Mater Process Technol 183(2–3):412–418

    Article  Google Scholar 

  8. Ghita OR, Baker DC, Evans KE (2008) An in-line near-infrared process control tool for monitoring the effects of speed, temperature, and polymer colour in injection moulding. Polym Test 27(4):459–469

    Article  Google Scholar 

  9. Collell, Castanyer and Josep (2006) Pigment preparation for coloring polymers NewAuthor1Collell, Castanyer, United States Patent PCT/ES2005/000347 (7,935,747 B2)

  10. Park K, Ahn J-H (2004) Design of experiment considering two-way interactions and its application to injection molding processes with numerical analysis. J Mater Process Technol 146(2):221–227

    Article  MathSciNet  Google Scholar 

  11. Boronat T, Segui VJ, Peydro MA, Reig MJ (2009) Influence of temperature and shear rate on the rheology and processability of reprocessed ABS in injection molding process. J Mater Process Technol 209(5):2735–2745

    Article  Google Scholar 

  12. Chen C-P, Chuang M-T, Hsiao Y-H, Yang Y-K, Tsai C-H (2009) Simulation and experimental study in determining injection molding process factors for thin-shell plastic parts via design of experiments analysis. Expert Syst Appl 36(7):10752–10759

    Article  Google Scholar 

  13. Ohta N, Robertson A (2006) Colorimetry: fundamentals and applications, 1st edn. Wiley, New York, pp 115–130

    Book  Google Scholar 

  14. Hunt RWG (2007) Colorimetry: understanding the CIE System, 1st edn. Wiley, New York, pp 61–64

    Google Scholar 

  15. Meza O, Diaz-Torres LA, Salas P, De la Rosa E, Solis D (2010) Color tunability of the upconversion emission in Er-Yb doped the wide band gap nanophosphors ZrO2 and Y2O3. Mater Sci Eng: B 174(1–3):177–181

    Article  Google Scholar 

  16. Duncan DR (1940) The colour of pigment mixtures. Proc Phys Soc 52(3):390

    Article  Google Scholar 

  17. Barron V, Torrent J (1986) Use of the Kulbelka-Munk theory to study the influence of iron oxides on soil colour. J Soil Sci 37:499–510

    Article  Google Scholar 

  18. Montgomery DC (2004) Design and analysis of experiments, 6th edn. Wiley, New York, pp 303–350

    Google Scholar 

  19. Allen TT (2006) Introduction to Engineering statistics and six sigma, statistical quality control and design of experiments and systems, 1st edn. Springer, Heidelberg, pp 259–277

    MATH  Google Scholar 

  20. Anderson DR, Sweeney DJ, Williams TA (2010) Statistics for business and economics, 11th edn. South-Western College, Chula Vista, pp 490–515

    Google Scholar 

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Correspondence to Octavio Meza.

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Meza, O., Vega, E. & Pérez, E. Influential factors on the outer lens color in an industrial injection molding process. Int J Adv Manuf Technol 66, 455–460 (2013). https://doi.org/10.1007/s00170-012-4340-8

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  • DOI: https://doi.org/10.1007/s00170-012-4340-8

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