Numerical optimization of process parameters in plastic injection molding for minimizing weldlines and clamping force using conformal cooling channel

Kitayama, Satoshi; Tamada, Kanako; Takano, Masahiro; Aiba, Setsuya

doi:10.1016/j.jmapro.2018.04.007

Cited by 51 publications

(33 citation statements)

References 40 publications

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“…Recently, multiobjective optimization was applied on steel case hardening to solve the trade-off between hardness and residual stresses [55]. The trade-off between minimum weldline temperature and clamping force in plastic injection moulding was also solved through multi-objective optimization [56].…”

Section: Normalized Normal Constraint Multi-objective Optimization Mementioning

confidence: 99%

Multi-objective robust design of helical milling hole quality on AISI H13 hardened steel by normalized normal constraint coupled with robust parameter design

Pereira

Silva

Lauro

et al. 2019

Applied Soft Computing

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Helical milling is a hole-making process which has been applied in hardened materials. Due to the difficulties on achieving high-quality boreholes in these materials, the influence of noise factors, and multi-quality performance outcomes, this work aims the multi-objective robust design of hole quality on AISI H13 hardened steel. Experiments were carried out through a central composite design considering process and noise factors. The process factors were the axial and tangential feed per tooth of the helix, and the cutting velocity. The noise factors considered were the tool overhang length, the material hardness and the borehole height of measurement. Response models were obtained through response surface methodology for roughness and roundness outcomes. The models presented good explanation of data variability and good prediction capability. Mean and variance models were derived through robust parameter design for all responses. Similarity analysis through cluster analysis was realised, and average surface roughness and total roundness were selected to multi-objective optimisation. Mean square error optimisation was performed to achieve bias and variance minimization. Multi-objective optimisation through normalized normal constraint was performed to achieve a robust Pareto set for the hole quality outcomes. The normalized normal constraint optimisation results outperformed the results of other methods in terms of evenness of the Pareto solutions and number of Pareto optimal solutions. The most compromise solution was selected considering the lowest Euclidian distance to the utopia point in the normalized space. Individual and moving range control charts were used to confirm the robustness achievement with regard to noise factors in the most compromise Pareto optimal solution. The methodology applied for robust modelling and optimisation of helical milling of AISI H13 hardened steel was confirmed and may be applied to other manufacturing processes. KeywordsHelical milling; AISI H13 hardened steel; Multi-objective robust optimization; Robust parameter design; Normalized normal constraint method. R 2 coefficient of determinationRadj 2 adjusted coefficient of determination Radj 2 prediction coefficient of determination

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Section: Normalized Normal Constraint Multi-objective Optimization Mementioning

confidence: 99%

Multi-objective robust design of helical milling hole quality on AISI H13 hardened steel by normalized normal constraint coupled with robust parameter design

Pereira

Silva

Lauro

et al. 2019

Applied Soft Computing

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“…The results confirmed that conformal cooling is effective due to the short cycle time and the warpage reduction. Kitayama et al [21] performed a multi-objective design optimization in order to maximize the minimum weld line temperature for weld lines reduction and to minimize the clamping force, achieving as a result an increase in the quality of the product. Park et al [22] presented the development of an injection mold with conformal cooling channels for manufacturing a free form industrial component with variable thickness.…”

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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“…Li et al [4] discussed the impact of cavity surface temperature on the surface topography and texture of molded reinforced plastic parts, and it was shown that the increase of cavity surface temperature can improve the surface appearance of the injected parts. Recently, literatures [5][6][7][8] focusing on the influences of mold temperature and other parameters on the weldline properties are also attracting more attention. However, concerning the relationship between the mold temperature and the part performances, there are still many problems that are not clear.…”

Section: Introductionmentioning

confidence: 99%

Advances in Polymer Technology Application of Pareto-Based Genetic Algorithm in Determining Layout of Heating Rods for a Plastic Injection Mold

Gong

Wang

et al. 2020

Advances in Polymer Technology

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The Pareto-based genetic algorithm is an effective way to solve complex optimization design problems in engineering. In this study, first, the principles of Pareto optimal solutions and multiobjective genetic algorithm were presented. Second, to investigate the influence of the mold temperature on the products’ performances, a multicavity experiment injection mold was designed whose temperature could be controlled by the heating rods. To obtain a homogeneous temperature distribution across the multicavity surfaces after the heating stage, multiobjective optimization models for the heating rods layout were established based on the heat transfer process of the mold. Finally, the Pareto-based genetic algorithm and finite element method were combined to solve the optimized models to obtain the optimal solution. After a finite element analysis and experimental injection, it is proved that the optimized distribution of the heating rods in the mold is necessary for the experiment and production.

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Numerical optimization of process parameters in plastic injection molding for minimizing weldlines and clamping force using conformal cooling channel

Cited by 51 publications

References 40 publications

Multi-objective robust design of helical milling hole quality on AISI H13 hardened steel by normalized normal constraint coupled with robust parameter design

Multi-objective robust design of helical milling hole quality on AISI H13 hardened steel by normalized normal constraint coupled with robust parameter design

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

Advances in Polymer Technology Application of Pareto-Based Genetic Algorithm in Determining Layout of Heating Rods for a Plastic Injection Mold

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