Production of thermoplastic compound materials for processing by injection molding, blow molding and extrusion

Katsevman, M. L.; Павлов, А. В.; Kruglov, P. V.

doi:10.1016/j.repl.2017.11.009

Cited by 2 publications

(2 citation statements)

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“…China has become the largest plastic consumption country in the world 1 . Injection molding technology is a processing technology that transforms thermoplastic and thermosetting materials into plastic products 2 . As the working machine tool for processing plastics, injection molding machines (IMMs) occupy a very important position in the national economy.…”

Section: Introductionmentioning

confidence: 99%

“…1 Injection molding technology is a processing technology that transforms thermoplastic and thermosetting materials into plastic products. 2 As the working machine tool for processing plastics, injection molding machines (IMMs) occupy a very important position in the national economy. IMMs are used as professional working machines for processing plastic parts and other plastics industries and almost 70% of plastic parts are produced by them.…”

Section: Introductionmentioning

confidence: 99%

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Deep learning‐based optimal tracking control of flow front position in an injection molding machine

Ren

Xie

et al. 2021

Optim Control Appl Methods

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The product quality of injection‐molded plastic is closely related to the injection flow velocity of molten plastics. In this article, an optimal tracking control problem for the injection flow front position arising in the filling process in the injection molding machine (IMM) is considered, and an intelligent real‐time optimal control method based on deep neural networks (DNNs) is developed for the online tracking of the flow front position to improve the efficient production process of the plastics. To this end, a highly nonlinear dynamic model describing the filling process is first proposed and then an optimal control problem is formulated. A high‐fidelity numerical optimization approach known as the Gauss pseudospectral method is used to numerically obtain the optimal state‐control solutions, which can then be saved as a huge training data set for the DNNs. The DNNs architecture is then developed and offline trained using the obtained data set to determine the best state–control relationship. As a consequence, the well‐trained DNN may be utilized to produce the matching optimum feedback action on‐board. Numerical studies are also carried out to verify the performance of our proposed approach.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Deep learning‐based optimal tracking control of flow front position in an injection molding machine

Ren

Xie

et al. 2021

Optim Control Appl Methods

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A Water-Soluble Core for Manufacturing Hollow Injection-Molded Products

Lin

Yang

2022

Polymers

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To manufacture a complicated hollow product without any assembly process, for example, the plastic intake manifold, is difficult by the traditional injection molding method. The fusible-core technique, which uses a low-melting-point alloy as a sacrificial core, was developed to solve this problem; however, the limited selection of resin type and the huge capital investment have caused this technique to spread slowly. In this work, a novel method is established that can produce similar products without the limitation of resin type, as well as a lower-energy-consumption process. The concept of the enveloped core defined by a water-soluble core assembled with a shell is proposed herein; it provides both rigidity and toughness to resist the pressure during the injection molding process. The shape of the enveloped core equals the internal contour of the designated product. An insert molding process was introduced to cover the enveloped core with a skin layer. Cut out the end of the enveloped core and immerse it into a water bath. When the water-soluble core inside the shell is dissolved, the product with a special internal contour is accomplished. A tee-joint is presented to demonstrate how the proposed method can be utilized. The optimal ingredient of the core and processing parameters are determined by the Taguchi method. The result shows that the proposed product is molded successfully when the compressive strength of the core is larger than 2 MPa. In addition, the eccentricity measurement of internal contour of the optimal sample exhibits a 56% improvement, and the required time for the core removal is less than 154 s.

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Production of thermoplastic compound materials for processing by injection molding, blow molding and extrusion

Cited by 2 publications

References 0 publications

Deep learning‐based optimal tracking control of flow front position in an injection molding machine

Deep learning‐based optimal tracking control of flow front position in an injection molding machine

A Water-Soluble Core for Manufacturing Hollow Injection-Molded Products

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