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Optimal design of medium channels for water-assisted rapid thermal cycle mold using multi-objective evolutionary algorithm and multi-attribute decision-making method

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Abstract

Rapid heat cycle molding technology developed recently is a novel polymer injection molding process. In this study, a new water-assisted rapid heat cycle molding (WRHCM) mold used for producing a large-size air-conditioning plastic panel was investigated. Aiming at improving heating efficiency and temperature distribution uniformity of the mold cavity surface, a two-stage optimization approach was proposed to determine the optimal design parameters of medium channels for the WRHCM mold. First of all, the non-dominated sorting genetic algorithm-II (NSGA-II) combined with surrogate models was employed to search the Pareto-optimal solutions. Subsequently, the Technique for Order Preference by Similarity to Ideal Solution was adopted as a multi-attribute decision-making method to determine the best compromise solution from the Pareto set. Then, the layout of the medium channels for this air-conditioning panel WRHCM mold was optimized based on the developed optimization method. It was indicated that the heating efficiency and temperature distribution uniformity on the mold cavity surface were greatly improved by using the optimal design results. Furthermore, the effectiveness of the optimization method proposed in this study was validated by an industrial application.

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References

  1. Čatić IJ (1979) Cavity temperature—an important parameter in the injection molding process. Polym Eng Sci 19:893–899

    Article  Google Scholar 

  2. Pisciotti F, Boldizar A, Rigdahl M, Arino I (2005) Effects of injection-molding conditions on the gloss and color of pigmented polypropylene. Polym Eng Sci 45:1557–1567

    Article  Google Scholar 

  3. Modesti M, Lorenzetti A, Bon D, Besco S (2005) Effect of processing conditions on morphology and mechanical properties of compatibilized polypropylene nanocomposites. Polym 46:10237–10245

    Article  Google Scholar 

  4. Chang RY, Tsaur BD (1995) Experimental and theoretical studies of shrinkage, warpage, and sink marks of crystalline polymer injection molded parts. Polym Eng Sci 35:1222–1230

    Article  Google Scholar 

  5. Hamada H, Tsunasawa H (1996) Correlation between flow mark and internal structure of thin PC/ABS blend injection moldings. J Appl Polym Sci 60:353–362

    Article  Google Scholar 

  6. An CC, Chen RH (2008) The experimental study on the defects occurrence of SL mold in injection molding. J Mater Process Technol 201:706–709

    Article  Google Scholar 

  7. Nakao M, Tsuchiya K, Sadamitsu T, Ichikohara Y, Ohba T, Ooi T (2008) Heat transfer in injection molding for reproduction of sub-micron-sized features. Int J Adv Manuf Technol 38:426–432

    Article  Google Scholar 

  8. Zhao J, Mayes RH, Chen G, Xie H, Chan PS (2003) Effects of process parameters on the micro molding process. Polym Eng Sci 43:1542–1554

    Article  Google Scholar 

  9. Yao DG, Kim B (2002) Development of rapid heating and cooling systems for injection molding applications. Polym Eng Sci 42:2471–2481

    Article  Google Scholar 

  10. Yao DG, Chen SC, Kim BH (2009) Rapid thermal cycling of injection molds: an overview on technical approaches and applications. Adv Polym Technol 27:233–255

    Article  Google Scholar 

  11. Chen SC, Peng HS, Chang JA, Jong WR (2004) Simulations and verifications of induction heating on a mold plate. Int Commun Heat Mass Trans 31:971–980

    Article  Google Scholar 

  12. Chang PC, Hwang SJ (2006) Simulation of infrared rapid surface heating for injection molding. Int J Heat Mass Transfer 49:3846–3854

    Article  MATH  Google Scholar 

  13. Chen SC, Chien RD, Lin SH, Lin MC, Chang JA (2009) Feasibility evaluation of gas-assisted heating for mold surface temperature control during injection molding process. Int Comm Heat Mass Trans 36:806–812

    Article  Google Scholar 

  14. Jeng MC, Chen SC, Minh PS, Chang JA, Chung CS (2010) Rapid mold temperature control in injection molding by using steam heating. Int Commun Heat Mass Trans 37:1295–1304

    Article  Google Scholar 

  15. Wang GL, Zhao GQ, Li HP, Guan YJ (2010) Research of thermal response simulation and mold structure optimization for rapid heat cycle molding processes, respectively, with steam heating and electric heating. Mater Design 31:382–395

    Article  Google Scholar 

  16. Li XP, Zhao GQ, Guan YJ, Ma MX (2009) Optimal design of heating channels for rapid heating cycle injection mold based on response surface and genetic algorithm. Mater Design 30:4317–4323

    Article  Google Scholar 

  17. Li XP, Zhao GQ, Guan YJ, Li HP (2009) Research on thermal stress, deformation, and fatigue lifetime of the rapid heating cycle injection mold. Int J Adv Manuf Technol 45:261–275

    Article  Google Scholar 

  18. Li XB (2009) Study of multi-objective optimization and multi-attribute decision-making for dynamic economic emission dispatch. Electr Power Compon Syst 37:1133–1148

    Article  Google Scholar 

  19. Lin YK, Yeh CT (2012) Multi-objective optimization for stochastic computer networks using NSGA-II and TOPSIS. Eur J Oper Res 218:735–746

    Article  MathSciNet  MATH  Google Scholar 

  20. Wei L, Yang YY (2008) Multi-objective optimization of sheet metal forming process using Pareto-based genetic algorithm. J Mater Process Technol 208:499–506

    Article  Google Scholar 

  21. Li XP, Zhao GQ, Guan YJ, Ma MX (2010) Multi-objective optimization of heating channels for rapid heating cycle injection mold using Pareto-based genetic algorithm. Polym Advan Technol 21:669–678

    Article  Google Scholar 

  22. Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE T Evolut Comput 6:182–197

    Article  Google Scholar 

  23. Kalyanmoy D (2001) Multi-objective optimization using evolutionary algorithms. Wiley, Singapore

    MATH  Google Scholar 

  24. Box GEP, Draper NR (1987) Empirical model-building and response surface. Wiley, New York

    Google Scholar 

  25. Ozcelik B, Erzurumlu T (2005) Determination of effecting dimensional parameters on warpage of thin shell plastic parts using integrated response surface method and genetic algorithm. Int Commun Heat Mass Trans 32:1085–1094

    Article  Google Scholar 

  26. McKay MD, Beckman RJ, Conover WJ (1979) A comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics 21:239–245

    MathSciNet  MATH  Google Scholar 

  27. Hwang CL, Yoon K (1981) Multiple attribute decision making: methods and applications. Springer, New York

    Book  MATH  Google Scholar 

  28. Deng H, Yeh CH, Willis RJ (2000) Inter-company comparison using modified TOPSIS with objective weights. Comput Oper Res 27:963–973

    Article  MATH  Google Scholar 

  29. Ma J, Fan ZP, Huang LH (1999) A subjective and objective integrated approach to determine attribute weights. Eur J Oper Res 112:397–404

    Article  MATH  Google Scholar 

  30. Shemshadi A, Shirazi H, Toreihi M, Tarokh MJ (2011) A fuzzy VIKOR method for supplier selection based on entropy measure for objective weighting. Expert Syst Appl 38:12160–12167

    Article  Google Scholar 

  31. Hsu PF, Hsu MG (2008) Optimizing the information outsourcing practices of primary care medical organizations using entropy and TOPSIS. Qual Quant 42:181–201

    Article  Google Scholar 

  32. Byun HS, Lee KH (2005) A decision support system for the selection of a rapid prototyping process using the modified TOPSIS method. Int J Adv Manuf Technol 26:1338–1347

    Article  Google Scholar 

  33. Wang GL, Zhao GQ, Li HP, Guan YJ (2010) Analysis of thermal cycling efficiency and optimal design of heating/cooling systems for rapid heat cycle injection molding process. Mater Design 31:3426–3441

    Article  Google Scholar 

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Correspondence to Jingjing Dong.

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Wang, M., Dong, J., Wang, W. et al. Optimal design of medium channels for water-assisted rapid thermal cycle mold using multi-objective evolutionary algorithm and multi-attribute decision-making method. Int J Adv Manuf Technol 68, 2407–2417 (2013). https://doi.org/10.1007/s00170-013-4868-2

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  • DOI: https://doi.org/10.1007/s00170-013-4868-2

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