Characterization of viscous response of a polymer during fabric IMD injection process by means a spiral mold

Martínez, A.; Castany, Javier; Mercado, Daniel

doi:10.1016/j.measurement.2011.09.011

Cited by 12 publications

(5 citation statements)

References 9 publications

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“…Fernandez [22][23] developed a tool to characterize frozen layer fraction of the polymer flow taking into account thermal conductivity of the boundary surfaces of the flow. These two researches are used by Martinez et al [24] to obtain some rheological characteristics of a single polymer-textile combination.…”

Section: Figure 5: Stressed Film During the Injection Processmentioning

confidence: 99%

Textile injection process characterisation by means of a spiral mould

et al. 2014

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Section: Figure 5: Stressed Film During the Injection Processmentioning

confidence: 99%

Textile injection process characterisation by means of a spiral mould

et al. 2014

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“…Also, spiral shape fiber was created without mask, lithography or direct printing which are expensive and time consuming. Spiral shape fiber was created in single step process for various applications such as cell patterning (Martinez et al 2011, Chen et al 2015, Paek et al 2015, Mecozzi et al 2016.…”

Section: Introductionmentioning

confidence: 99%

Silicon micro pyramidal syringe array for electrospinning spiral shape single fiber

Masouleh

Moghadam

Koohsorkhi

2020

Mater. Res. Express

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In this study, a new method is presented to fabricate spiral shape single fiber. The micro-needle array (40 μm hole diameter, 80 μm outer diameter, and 100 μm height) is utilized instead of the needle to reduce the diameter of fibers which are electrospun from 23Wt% PVP concentration. In order to have fine and bead-free fibers, the structural parameters of the micro-needle array and space which close microneedles act as an individual one are simulated. The Wet and Dry Etching techniques are used for fabrication of micro-needles. The experimental setup consists of the stepper motor and micrometer head as the pump, distance controller, and voltage generator. The single fiber can be electrospun by applying 1-3 kV bias within 1 mm gap between micro-needle and collector. Using nonconductive collector causes the formation of spiral type single fiber instead of agglomerate fiber. Elastic and expulsion forces in charged fibers seem to be the main reasons of fiber separation and spiral shape formation. The spiral shape fiber is made without traditional lithography techniques like direct patterning or contact exposure which are more expensive and time-consuming. The alteration in the fiber pattern can be seen by changing the applied voltage and spinneret, microneedle and needle. After various experiments, spirality pattern electrospun by microneedle with 10-15 μm and 15-35 μm distribution area of first and second circles and 500-570 nm and 570-660 nm diameter of first and second circles is gained as the structure with minimum distribution area and fiber width. This structure is created when the applied voltage and distance between microneedle and collector are 1kV and 1 mm.

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“…However, the researches cited above mostly optimized the process parameters that minimize the warpage or/and shrinkage of the parts, whereas the flow behavior greatly affecting the quality of the injection molding parts was rarely taken into consideration [26][27][28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Prediction of Polymer Flow Length by Coupling Finite Element Simulation with Artificial Neural Network

Sandu¹,

Susac²,

Stan³

et al. 2020

Mater. Plast.

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In this study, computer-aided engineering (CAE) simulation software and the design of experiments (DOE) method were used to simulate the injection molding process in terms of the melt flow length, using a spiral part. Process parameters such as melt temperature, mold temperature, injection pressure and mold cavity thickness were considered as injection molding variables. A predictive model for the flow length was created using a three-layer artificial neural network (ANN). The ANN model was trained with both simulation and experimental data, and the predictive performances were compared in terms of correlation coefficient, root mean square error and mean relative error. The cavity thickness and melt temperature were found to be the most significant factors for both the simulation and the experiment, while the injection pressure and the mold temperature had little effect on the flow length. The ANN model trained with Moldex3D data shows a significantly higher prediction capacity than the ANN model trained with experimental data. However, the melt flow lengths predicted by the ANN model for both Moldex3D and Moldflow simulation data are statistically significant, indicating that the proposed prediction methodology, which combines the ANN model, DOE method and the CAE simulation technology, can effectively predict the flow length of injection molded parts, with a small number of data.

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Characterization of viscous response of a polymer during fabric IMD injection process by means a spiral mold

Cited by 12 publications

References 9 publications

Textile injection process characterisation by means of a spiral mould

Textile injection process characterisation by means of a spiral mould

Silicon micro pyramidal syringe array for electrospinning spiral shape single fiber

Prediction of Polymer Flow Length by Coupling Finite Element Simulation with Artificial Neural Network

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