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 method and system for co-injection molding of two molten plastic materials that allows monitoring and utilization of injection pressure and optionally melt pressure and/or flow front pressure during an injection run. A controller alters the injection pressure so as to achieve and maintain optimal or desired ratios of injection pressure, and optionally melt pressure and/or flow front pressure, of the two molten plastic materials. This allows for more precise part manufacture, including reducing the thickness of a skin or shell layer compared to a core layer of a molded part.

An apparatus for assisting resin molding, including: a calculation unit for calculating, for each of a plurality of molding factors of the resin molding, a degree of influence on an analysis target characteristic of a resin molded article; a selection unit for selecting, based on the degree of influence, at least one molding factor among the plurality of molding factors; and a display processing unit for executing display processing for causing the selected at least one molding factor to be emphasized on a display of the plurality of molding factors displayed by the display device, is provided.

Provided is an apparatus configured to support resin molding, including: a prediction unit configured to generate a probability distribution of prediction values of analysis target characteristics of a resin molded body, that correspond to values of a plurality of molding factors of the resin molding; and a display processing unit configured to execute display processing for causing a display apparatus to display the probability distribution of the prediction values of the analysis target characteristics. The prediction unit is configured to calculate a change of the distribution of the prediction values of the analysis target characteristics when a value of at least one of the plurality of molding factors of the resin molding is changed within a predetermined range, and the display processing unit is configured to display the change of the probability distribution of the prediction values of the analysis target characteristics.

First training data including a set value related to a molding machine, a measured value obtained by measuring a physical quantity related to molding, and a degree of quality of a molded product generated by the molding machine is collected, a first learning model for outputting a degree of quality of a molded product when a set value and a measured value are input is generated by machine learning based on collected first training data, second training data including a defect degree for each defect type of a molded product, a measured value, and a set value capable of reducing the defect degree is collected, and a second learning model for outputting a set value capable of reducing a defect degree when a defect degree and a measured value are input is generated by machine learning based on collected second training data and a degree of quality output from the first learning model.

A molding machine management device that is able to couple to a molding machine includes a storage unit configured to store, in chronological order, numerical value information on a molding process when a molded product is molded by the molding machine and four-factor information on four factors of production which includes a man, a machine, a material, and a method when the molded product is produced, and an output control unit configured to classify the numerical value information into a plurality of groups for periods divided according to time when the four factors of production changes, and output the numerical value information classified into the plurality of groups to an output unit in group units.

Provided is an apparatus for taking out a molded product capable of displaying information for facilitating adjustment on a display screen when performing adjustment for shortening a take-out time and a cycle time. The apparatus for taking out a molded product includes: a set condition storing section; an operation time counting section operable to count an actual operation time from a time when a plurality of set operations are started till a time when the operations are completed; an operation time storing section operable to store, the plurality of actual operation times counted by the operation time counting section; a display section including a display screen; a display control section; and a data computing section. The display control section displays on the display screen identification indications for a plurality of set operations, set values for the set operations, and the actual operations times stored in the operation time storing section.

A state determination device acquires data on an injection molding machine and stores conditions for classifying the acquired data on the injection molding machine and a plurality of learning models. The state determination device further classifies the acquired data based on the stored classification conditions and settles a learning model to which the classified data are applied, among the plurality of stored learning models. Subsequently, the state determination device performs machine learning for the learning model settled as an application destination, based on the classified data.

A method of classifying a temperature control branch of a molding toolincludes producing molded parts in cycles by a portion of the molding tool by introducing heat into the molding tool, and/or cyclically activating a heating device, with introduction of heat into the molding tool, conveying temperature control medium through the temperature control branch of the molding tool to dissipate the introduced heat, measuring a temporal branch temperature profile of the temperature control medium in the temperature control branch over several production cycles, analyzing a curve behavior of the branch temperature profile and/or of a variable derived from the branch temperature profile, in particular of a branch heat flow, over several production cycles, and sorting the temperature control branch into one of at least two categories, according to greater and/or smaller influence on the heat budget of the portion of the molding tool, on the basis of the curve behavior.

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.