Multi-objective optimization of injection molding process parameters for short cycle time and warpage reduction using conformal cooling channel

Kitayama, Satoshi; Miyakawa, Hiroyasu; Takano, Masahiro; Aiba, Setsuya

doi:10.1007/s00170-016-8904-x

Cited by 118 publications

(53 citation statements)

References 34 publications

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“…The effect of para-conformal cooling on the temperature development of the IM inserts is shown in Figure 3 (step 2a) and Figure 4 (step 2b) whereas the para-conformal cooling approach will allow for a shorter cooling time as the cooling temperature is already lower at the time of ejection. This conforms with research like [6] where the authors claim to reach an improvement of cycle time due to conformal cooling by 53 %. The development steps 3a and 3b elaborate on the fact that fiber-reinforced PhP IM inserts provide a longer lifetime.…”

Section: Resultssupporting

confidence: 91%

Evolution of additively manufactured injection molding inserts investigated by thermal simulations

Hofstätter¹,

Pedersen²,

Tosello³

et al. 2019

AIP Conference Proceedings

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Injection molding using inserts from vat polymerization, an additive manufacturing technology, has been investigated for pilot production and rapid prototyping purposes throughout the past years. A standard mold is equipped with additively manufactured inserts in a rectangular shape of (20 x 20 x 2.7) mm 3 and (60 x 80 x 10) mm 3 produced with vat photo polymerization. This contribution discusses the heat transportation within the inserts made from a thermoset material, brass, steel, and ceramic material. It therefore elaborates on the possibilities of injection molding as well as the thermal challenges connected with the use of polymer inserts. They are an essential part for further calibrations of the injection molding process, which suffers from reduced lifetime due to the poor thermal conductivity of polymer inserts as compared to metal inserts. Multiscale inserts combining micro features at larger inserts in the cm-range.

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Section: Resultssupporting

confidence: 91%

Evolution of additively manufactured injection molding inserts investigated by thermal simulations

Hofstätter¹,

Pedersen²,

Tosello³

et al. 2019

AIP Conference Proceedings

View full text Add to dashboard Cite

show abstract

“…Warpage and cycle time [128,129] Shrinkage and clamping force [130] Warpage [131] function to the resulting sum in order to determine the output. e ANN learns to approximate the functions through a training process and adjusts their weights and biases until a performance index reaches a preset threshold value.…”

Section: Taguchi Methodmentioning

confidence: 99%

“…e ANN learns to approximate the functions through a training process and adjusts their weights and biases until a performance index reaches a preset threshold value. Kitayama et al [128,129] developed an injection mold with a conformal cooling channel, combined with computer simulation, using a radial basis function network for multiobjective optimization of the injection process. e cycle time improved by 26%, and the warpage improved by 14% using an optimal combination of process parameters.…”

Section: Taguchi Methodmentioning

confidence: 99%

Intelligent Injection Molding on Sensing, Optimization, and Control

Zhao

Zhang

Dong

et al. 2020

Advances in Polymer Technology

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Injection molding is one of the most significant material processing methods for mass production of plastic products. It is widely used in various industry sectors, and its products are ubiquitous in our daily life. The settings and optimization of the injection molding process dictate the geometric precision and mechanical properties of the final products. Therefore, sensing, optimization, and control of the injection molding process have a crucial influence on product quality and have become an active research field with abundant literature. This paper defines the concept of intelligent injection molding as the integral application of these three procedures—sensing, optimization, and control. This paper reviews recent studies on methods for the detection of relevant physical variables, optimization of process parameters, and control strategies of machine variables in the molding process. Finally, conclusions are drawn to discuss future research directions and technologies, as well as algorithms worthy of being explored and developed.

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“…The sensitivity analysis together with boundary element method presented a good performance; however, they are not applicable to real industrial parts. Kitayama et al [20] examined the cooling design of conformal channels, analyzing the cycle time and the warpage in industrial molded parts through numerical and experimental tests. The results confirmed that conformal cooling is effective due to the short cycle time and the warpage reduction.…”

Section: Background and Related Workmentioning

confidence: 99%

A New Conformal Cooling Design Procedure for Injection Molding Based on Temperature Clusters and Multidimensional Discrete Models

et al. 2020

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This paper presents a new method for the automated design of the conformal cooling system for injection molding technology based on a discrete multidimensional model of the plastic part. The algorithm surpasses the current state of the art since it uses as input variables firstly the discrete map of temperatures of the melt plastic flow at the end of the filling phase, and secondly a set of geometrical parameters extracted from the discrete mesh together with technological and functional requirements of cooling in injection molds. In the first phase, the algorithm groups and classifies the discrete temperature of the nodes at the end of the filling phase in geometrical areas called temperature clusters. The topological and rheological information of the clusters along with the geometrical and manufacturing information of the surface mesh remains stored in a multidimensional discrete model of the plastic part. Taking advantage of using genetic evolutionary algorithms and by applying a physical model linked to the cluster specifications the proposed algorithm automatically designs and dimensions all the parameters required for the conformal cooling system. The method presented improves on any conventional cooling system design model since the cooling times obtained are analogous to the cooling times of analytical models, including boundary conditions and ideal solutions not exceeding 5% of relative error in the cases analyzed. The final quality of the plastic parts after the cooling phase meets the minimum criteria and requirements established by the injection industry. As an additional advantage the proposed algorithm allows the validation and dimensioning of the injection mold cooling system automatically, without requiring experienced mold designers with extensive skills in manual computing.

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Multi-objective optimization of injection molding process parameters for short cycle time and warpage reduction using conformal cooling channel

Cited by 118 publications

References 34 publications

Evolution of additively manufactured injection molding inserts investigated by thermal simulations

Evolution of additively manufactured injection molding inserts investigated by thermal simulations

Intelligent Injection Molding on Sensing, Optimization, and Control

A New Conformal Cooling Design Procedure for Injection Molding Based on Temperature Clusters and Multidimensional Discrete Models

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