Optimal cooling system design for multi-cavity injection molding

Tang, Li Qiang; Chassapis, Constantin; Manoochehri, Souran

doi:10.1016/s0168-874x(96)00083-2

Cited by 76 publications

(54 citation statements)

References 13 publications

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“…2,5,6,21 It is also apparent from the different results obtained in each case that the mold surface temperature affects significantly the cooling time prediction.…”

Section: Amorphous Polymersmentioning

confidence: 98%

Prediction of cooling time in injection molding by means of a simplified semianalytical equation

Zarkadas

Xanthos

2003

Adv Polym Technol

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ABSTRACT:A simplified semianalytical equation, used successfully in food freezing/chilling time prediction, is proposed as a potential simple alternative for cooling time prediction in injection molding of polymer parts, amorphous or semicrystalline. This equation is based on a convective boundary condition for the mold-part interface and requires information on the thermal contact resistance (TCR) or thermal contact conductance (TCC) at this interface, as well as information on the initial and final product temperatures, the mold surface temperature, and the thermal properties of the part. Eighty-five data points for four polymers, Polystyrene (PS), Polycarbonate (PC), Polypropylene (PP), and Polyethylene (PE) were generated with C-MOLD TM , a commercial injection molding design software, and the performance of the proposed equation was tested. The % mean error and its standard deviation (SD) in cooling time prediction were, respectively, −11.61 and 2.27 for PS, −6.04 and 2.13 for PC, −7.27 and 6.55 for PP, and −8.88 and 2.93 for PE. It was also shown that the accuracy of PREDICTION OF COOLING TIME IN INJECTION MOLDINGthe proposed equation is not affected significantly by the exact knowledge of the TCC, provided that the latter is not smaller than 1000-2000 W m −2 K −1 . Since in this comparison all necessary temperatures were obtained from C-MOLD TM , methods of using the proposed equation independently were tested. The use of the inlet melt temperature as the initial product temperature increased the % mean error by mostly 1.5% while its SD remained practically the same. By incorporating a literature based heat balance method in the proposed equation, it was possible to use it as a stand-alone predictor of polymer cooling time. The % mean error and its SD calculated this way were, respectively, −9.44 and 0.97 for PS, −9.44 and 0.83 for PC, −14.22 and 5 for PP, and −20.12 and 1.38 for PE. The proposed equation, at least in a preliminary stage, can be used successfully to predict the cooling time of the selected semicrystalline or amorphous polymers with the accuracy being higher for amorphous polymers.

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“…2,5,6,21 It is also apparent from the different results obtained in each case that the mold surface temperature affects significantly the cooling time prediction.…”

Section: Amorphous Polymersmentioning

confidence: 98%

Prediction of cooling time in injection molding by means of a simplified semianalytical equation

Zarkadas

Xanthos

2003

Adv Polym Technol

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“…The cooling stage is of the greatest importance because it significantly affects the productivity and the quality of the final product. It is well known that more than seventy percent of the cycle time in the injection molding process is spent in cooling the hot polymer melt sufficiently so that the part can be ejected without any significant deformation [2]. An efficient cooling system design of the cooling channels aiming at reducing cycle time must minimize such undesired defects as sink marks, differential shrinkage, thermal residual stress built-up and part warpage.…”

Section: Introductionmentioning

confidence: 99%

Effect of cooling system on the polymer temperature and solidification during injection molding

Hassan

Régnier

Lebot

et al. 2009

Applied Thermal Engineering

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“…The first group focuses on how to optimize the configuration of the cooling system in terms of shape, size, and location of cooling lines (Tang et al, 1997;Park & Kwon, 1998;Lin, 2002;Rao et al, 2002;Lam et al, 2004;Qiao, 2005;Li et al, 2009;Zhou et al, 2009;Hassan et al, 2010). These studies used some of methods from semi-analytical method to finite difference, boundary element method (BEM), and finite element method (FEM).…”

mentioning

confidence: 99%

“…In addition, cooling design is often based on designer's experience and intuition. When molding geometry becomes more complex, experience-based and trial-and-error approaches would be timeconsuming and less feasible (Tang et al, 1997;Lin, 2002;Lam et al, 2004;Qiao, 2006).…”

mentioning

confidence: 99%

Design and simulation-based optimization of cooling channels for plastic injection mold

Park¹,

Dang²

2012

New Technologies - Trends, Innovations and Research

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Optimal cooling system design for multi-cavity injection molding

Cited by 76 publications

References 13 publications

Prediction of cooling time in injection molding by means of a simplified semianalytical equation

Prediction of cooling time in injection molding by means of a simplified semianalytical equation

Effect of cooling system on the polymer temperature and solidification during injection molding

Design and simulation-based optimization of cooling channels for plastic injection mold

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