A study of gate location optimization of plastic injection molding using sequential linear programming

Zhai, Mingyue; Xie, Yingbai

doi:10.1007/s00170-009-2376-1

Cited by 36 publications

(18 citation statements)

References 14 publications

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“…To limit the range of variation in the wall thickness and to avoid mesh penetrations that yield wall thicknesses near zero, each entry of the design vector x is constrained as follows: (16) where z min,i is the minimum z-location of the supporting point, P i , and z max,i is the maximum valid value of the same point. …”

Section: Definition Of the Optimization Problemmentioning

confidence: 99%

“…Therefore, optimizing the gate location is another effective method for reducing the warpage. [16][17][18][19][20][21] However, in many cases, there are strong restrictions on the gate location, especially for parts with complex shapes or for molds with many moving elements. Therefore, this method of optimizing the gate location is not always useful.…”

Section: Introductionmentioning

confidence: 99%

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Minimizing Part Warpage in Injection Molding by Optimizing Wall Thickness Distribution

Studer

Ehrig

2014

Adv Polym Technol

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ABSTRACT:The warpage of injection-molded parts is an omnipresent problem in new product development. In this study, a method is developed to reduce the warpage by optimizing the wall thickness distribution of a part. This method is based on an iterative optimization procedure consisting of mold flow analysis, a mesh parameterization tool for geometry manipulation, and an optimization algorithm. Starting with the initial design for the mold cavity, the procedure optimizes the wall thickness distribution at user-defined area sections within prescribed tolerances. A unit-square parameterization technique is applied that uses mean-valued coordinates and a second-order polynomial thickness distribution. Three different optimization algorithms-an evolutionary algorithm, a surrogate-based response surface method, and a direct search method-are considered, and the optimization performances of these algorithms are evaluated for a warpage demonstrator and real industrial part. The results demonstrate the effectiveness of the developed procedure and plausibility of the optimized thickness distribution. C

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Section: Definition Of the Optimization Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Minimizing Part Warpage in Injection Molding by Optimizing Wall Thickness Distribution

Studer

Ehrig

2014

Adv Polym Technol

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“…Altan [5] conducted experiments using the Taguchi method and ANOVA in an attempt to reduce injection molding shrinkage. Zhai and Xie [6], using the Moldflow software and the Taguchi method in injection molding, carried out optimization experiments to seek the optimal convoluted positions. In line with this, Ng et al [7] employed the Taguchi method and ANOVA in their attempt to optimize the injection molding process parameters.…”

Section: Introductionmentioning

confidence: 99%

Optimization of the plastic injection molding process using the Taguchi method, RSM, and hybrid GA-PSO

Chen

Nguyen

Chiu

et al. 2015

Int J Adv Manuf Technol

123

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This paper proposes a systematic optimization model of process parameters in plastic injection molding (PIM). Firstly, the Taguchi method is employed for experimentation and data analysis, in which the quality characteristics for the plastic injection product are length and warpage. The control factors for the process are melt temperature, injection velocity, packing pressure, packing time, and cooling time. Moreover, the signal-to-noise (S/N) ratio and analysis of variance (ANOVA) are used to obtain a combination of parameter settings. Experimental data are set for the response surface methodology (RSM) in order to analyze and create two quality predictors and two S/N ratio predictors. The two quality predictors are associated with genetic algorithms (GA) to search for an optimal combination of process parameters that meets multiple-objective quality characteristics. Finally, four predictors are combined with the hybrid GA-PSO to find the final optimal combination of process parameters. The confirmation results show that the proposed model not only enhances the stability in the injection molding process, including the quality in length and warpage, but also reduces the costs of and time spent in the PIM process.

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“…Additionally, the taguchi method in the extant literature just mainly utilizes S/N ratio to seek the initial process parameters (Wu and Chen, 2006;teng and Xu, 2008;Aggarwal et al, 2008;Kurt et al, 2009;Altan, 2010;Zhai and Xie, 2010;Ng et al, 2011;Öktem, 2012;Wang et al, 2013). However, the results of taguchi experiments which aimed at seeking the optimal process parameters remained discrete combinations, which in turns failed to find the optimal process parameters.…”

Section: Introductionmentioning

confidence: 93%

Study on the traditional method for communication between vlans of IoT based on education simulation technology

2015

Management, Information and Educational Engineering

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this paper proposes an optimization model of process parameters in Plastic Injection Molding (PIM). Firstly, the taguchi method is employed for experiment and data analysis in which the quality characteristics for the plastic injection product are length and warpage. Besides, the control factors for the process are melt temperature, injection velocity, packing pressure, packing time, and cooling time. Moreover, the signalto-noise (S/N) ratio and analysis of variance (ANOVA) are used to obtain a combination of parameter settings. Experimental data are set for the Response Surface Methodology (RSM) to analyze and create two quality predictors. two quality predictors, length and warpage, are associated with Genetic Algorithm (GA) to search for an optimal combination of process parameters that meets multiple-objective quality characteristics. the confirmation results show that the approach not only enhances the stability in the injection molding process including the quality in length and warpage but also saves the cost and time spent from the mold design to manufacturing.

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A study of gate location optimization of plastic injection molding using sequential linear programming

Cited by 36 publications

References 14 publications

Minimizing Part Warpage in Injection Molding by Optimizing Wall Thickness Distribution

Minimizing Part Warpage in Injection Molding by Optimizing Wall Thickness Distribution

Optimization of the plastic injection molding process using the Taguchi method, RSM, and hybrid GA-PSO

Study on the traditional method for communication between vlans of IoT based on education simulation technology

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