Nissei Plastic Industrial Co., Ltd.

Eiki Iwashita

Yoshitoshi Yamagiwa

Takayoshi Shioiri

Takashi Terashima

Takayoshi Shiori

A method for controlling injection molding using a neural network in a control device of an injection molding machine. A measurement monitor value is acquired in a measurement step during test injection molding and an injection monitor value is acquired in an injection step. The acquired measurement monitor value is designated as an input term and the injection monitor value is designated as an output term. A prediction function that incorporates the measurement monitor value is then determined using the neural network. A first value corresponding to the injection monitor value is predicted by substituting into the prediction function a measurement monitor value acquired at completion of a measurement step during mass-production injection molding. On the basis of the predicted first value, a second value corresponding to an injection condition is determined. Injection control and pressure maintenance control are then implemented on the basis of the second value corresponding to the injection condition.

Injection molding control method

A support apparatus of an injection-molding machine has a neural network that receives test molding data corresponding to molding conditions and a quality value obtained by measuring a non-defective molded article, and that determines a quality prediction function based on the received test molding data. A computer calculates a predicted value of the quality value using the quality prediction function. An input apparatus inputs into the neural network fixed values for the molding conditions except for a selected at least one of the molding conditions, and inputs a target value of the quality value. A graph generator generates a graphical relationship between the selected at least one molding condition and the predicted value. A graph correction unit corrects the graphical relationship generated by the graph generator on the basis of the target value. A display unit selectively displays the graphical relationship generated by the graph generator and the graphical relationship corrected by the graph correction unit.

Support apparatus of injection-molding machine

A provisional temperature estimating mathematical expression is set in accordance with which plasticizing conditions used as terms are to be multiplied by unknown coefficients. Then, a given number of experiments not smaller than the number of the unknown coefficients are conducted while the plasticizing conditions are varied, so as to acquire various experimental data. The unknown coefficients are converted into known coefficient in accordance with the acquired experimental data so as to provide a complete temperature estimating mathematical expression, on the basis of which a plasticized resin temperature and noise-outlet resin temperature are determined arithmetically.

Method for estimating temperatures of plasticized resin within heating cylinder and at nozzle outlet, and estimating injecting conditions

Test molding and mass-production molding are performed by an injection molding machine that includes a control apparatus in which neural networks are used. A quality prediction function determined based on the test molding is revised as necessary during mass-production molding.

Control apparatus for injection molding machine

Molding conditions of an injection molding machine are set through performance of virtual molding by CAE. First, actual molding is performed under provisional molding conditions in order to obtain an actual profile showing variation in load pressure actually measured during at least an injection step of the actual molding. Further, virtual molding is performed by CAE under the provisional molding conditions in order to obtain a virtual profile showing variation in load pressure simulated during at least an injection step of the virtual molding. The provisional molding conditions are changed by CAE in such a manner that the virtual profile coincides with the actual profile, to thereby obtain intermediate molding conditions. Subsequently, the intermediate molding conditions are optimized so as to obtain molding conditions for the injection molding machine.

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Nagano, Japan

Eiki Iwashita