An artificial intelligence-based injection molding system comprising a standard data extraction unit for extracting target standard data of a product produced by a mold from mold information about the mold to which a molding material is supplied; a molding condition output unit inputing the extracted target standard data into a pre-learned molding condition generation model to output a molding condition; an injection molding device, supplying the molding material to the mold according to the molding condition to produce the product; and a determination unit, comparing production standard data of the produced product and the target standard data to determine whether the molding condition is appropriate, wherein, if the determination unit determines that the molding condition is inappropriate, the molding condition output unit generates the production standard data and the molding condition as one set of feedback data, and trains the molding condition generation model with the set of feedback data.

Systems and approaches for controlling an injection molding machine and a mold forming a mold cavity and being controlled according to an injection cycle. The systems and methods include analyzing a model of at least one of the injection molding machine, the mold, and a molten material to determine initial values for one or more control parameters of the injection molding machine, and executing a run of injection cycles at the injection molding machine; measuring operation of the injection molding machine during a particular injection cycle of the run of injection cycles; determining one or more operational parameters exceed a threshold; and upon determining that the one or more operational parameters exceed the threshold, adjusting the one or more control parameters for subsequent injection cycles of the run of injection cycles.

A stepped flight is formed on a screw of an injection molding machine. The stepped flight is a flight in which a step-shaped step portion is formed on a top portion thereof. The top portion of the flight includes a large diameter portion on an upstream side and a land portion on a downstream side. When a gap ratio m of a gap H.sub.1 between the land portion and a bore of the heating cylinder to a gap H.sub.2 between the large diameter portion and the bore is defined as H.sub.1/H.sub.2, the gap ratio m is selected to be 2.3≤m≤6.4.

A system includes a cavity, an injection nozzle configured to inject material into the cavity, and a plurality of sensors at sensor locations. Each of the plurality of sensors is configured to measure parameters at one of the sensor locations. The system lacks a strain gauge. The system further includes a controller configured to control a flow rate of the injection of material into the cavity. The controller is configured to receive the measured parameters and compare the received information to predetermined curves. The controller is configured to control the flow rate when the measured parameters deviate from the predetermined curves.

A system includes a cavity, an injection nozzle configured to inject material into the cavity, and a plurality of sensors at sensor locations. Each of the plurality of sensors is configured to measure parameters at one of the sensor locations. The system lacks a strain gauge. The system further includes a controller configured to control a flow rate of the injection of material into the cavity. The controller is configured to receive the measured parameters and compare the received information to predetermined curves. The controller is configured to control the flow rate when the measured parameters deviate from the predetermined curves.

There is disclosed a method (400) of operating a molding system (100), the method (400) executable by a controller (140) of the molding system (100). The method comprises appreciating (402) a plurality of operational parameters associated with the molding system (100); based on at least a sub-set of the plurality of operational parameters, generating (404) a machine performance index, the machine performance index being a single value representative of the at least a sub-set of the plurality of operational parameters and being instrumental in enabling an operator of the molding system (100) to appreciate an economic productivity factor associated therewith; causing (406) the machine performance index to be displayed on an interface of the controller (140).

In an injection molding system, a molded part transport apparatus and a worker share an area to perform cooperative work. When a molded part check mode is valid, conforming product identification inspection of a molded part is performed in an area where the worker works, and molded part sorting means sorts the molded part on the basis of a result of the inspection. As a result, the conforming product identification inspection of the molded part can be performed and the molded part can be sorted with the safety of the worker is maintained.

The present application relates to an injection molding system, comprising: an input condition storage section 23 to store an input plasticization condition; an ideal plasticization state storage section 24 to store information of an ideal state of plasticization; an input condition simulation section 29 for the plasticization condition based on data stored in the input condition storage section 23; a comparison section 25 to compare the information stored in the ideal plasticization state storage section 24; an optimal condition analysis and calculation section 26 to calculate the optimal plasticization condition when the data stored in the input condition storage section 23 is decided not to be the ideal state of plasticization by the comparison section 25 using the data of the input condition storage section 23 and the information stored in the ideal plasticization state storage section 24; and a condition change indicating section 28 to display information necessary to make a change to the optimal plasticization condition on a display section 22 based on a result of calculation by the optimal condition determination section 26.

A device for assisting molding condition determination is used with a molding method that molds an article by feeding molten material into a mold. The device includes a learning model generating unit, an input unit, and an output unit. The learning model generating unit creates a learning model through machine learning in which a plurality of molding condition element items used to mold the article and a plurality of quality element items of the molded article are used as learning data. The learning model relates to a degree of influence of each molding condition element item on each quality element item. The input unit receives input of a subject quality element item to be checked, selected from the quality element items. The output unit outputs, using the learning model, the multiple molding condition element item that has the degree of influence on the subject quality element item.

Systems and approaches for controlling an injection molding machine and a mold forming a mold cavity and being controlled according to an injection cycle. The systems and methods include analyzing a model of at least one of the injection molding machine, the mold, and a molten material to determine initial values for one or more control parameters of the injection molding machine, and executing a run of injection cycles at the injection molding machine; measuring operation of the injection molding machine during a particular injection cycle of the run of injection cycles; determining one or more operational parameters exceed a threshold; and upon determining that the one or more operational parameters exceed the threshold, adjusting the one or more control parameters for subsequent injection cycles of the run of injection cycles.