A process generation system for generating a production process of a molded product produced by an injection molding machine or a press machine is provided. The process generation system includes: a specification information acquisition unit acquiring specification information about a specification of a molded product; a processing information selection unit selecting processing information about processing of the molded product, based on the specification information; a standard routing decision unit deciding a standard routing including a plurality of processes for producing the molded product, based on the processing information; and a routing editing unit rearranging the processes included in the standard routing and thus generating the production process, based on the specification information.

System and method for monitoring system parameters from multiple independent controllers that monitor and control an injection process is a plurality of IMSs, including: establishing a common graphical user interface (common GUI) for viewing system parameters of a tool based injection molding system (IMS), the IMS including a plurality of different local controllers that control different tool based system functions of the IMS and one common graphical user interface (local GUI) with GUI routines specific to the local controllers for set up and monitoring of the respective tool based system function of the respective local controllers.

It is an objective of the present invention to provide an injection molding machine capable of preventing a molding defect and a method of controlling the injection molding machine. An injection molding machine according to the present embodiment is an injection molding machine that molds a product for each execution of a molding cycle through an injecting process of injecting a material into clamped molds, a dwell process of controlling dwell pressure of the material in the molds, and a cooling process of cooling the material in the molds, the injection molding machine including a mold opening amount sensor and a controlling unit, the mold opening amount sensor being configured to detect a mold opening amount of the molds, the controlling unit being configured to control clamping force of the molds and the dwell pressure based on the mold opening amount during the molding cycle.

A control device of an injection molding machine, the injection molding machine including: a mold clamping device that advances and retracts a movable mold with respect to a fixed mold; and an injection device that injects and fills a molten material into a cavity formed between both the molds, the control device including: a display unit that displays a setting screen for setting molding conditions of the injection molding machine; and a setting unit that sets the molding conditions based on information displayed on the setting screen.

The present disclosure provides a method of measuring a true shear viscosity profile of a molding material in a capillary and a molding system performing the same. The method includes the operations of: determining a setpoint temperature of the molding material before injecting into the capillary; obtaining an initial shear viscosity profile at the setpoint temperature with respect to a shear rate of the molding material; fitting an initial temperature profile with respect to the shear rate according to the initial shear viscosity based on Cross William-Landel-Ferry model; fitting a first shear viscosity profile and a first temperature profile with respect to the shear rate according to the initial temperature profile based on the Cross-WLF model; and setting the first shear viscosity profile as the true shear viscosity profile when a difference between the first temperature profile and the initial temperature profile is not greater than a threshold.

A numerical control system detects a state amount indicating a state of an injection operation of an injection molding machine, generates a characteristic amount that characterizes the state of the injection operation from the state amount, and infers an evaluation value of the state of the injection operation from the characteristic amount. The numerical control system detects an abnormal state on the basis of the evaluation value, generates or updates a learning model by machine learning that uses the characteristic amount, and stores the learning model in correlation with a combination of conditions of the injection operation.

Certain exemplary embodiments can provide a method comprising, via computer aided design, designing parts of an object that comprises an outer shell and an inner body, at least one of the outer shell and the inner body defining a specific volume negative space relief. In certain exemplary embodiments, the specific volume negative space relief defines a channel constructed to pass at least one of a fluid and a gas.

An apparatus receives a first image of an object captured under a first light measurement condition and receives a second image of the object captured under a second light measurement condition. The apparatus determines a first transmission value of the object based on the first image, determines a second transmission value of the object based on the second image, and determines, based on a difference between the first transmission value and the second transmission value, a light scattering property of the object.

The present disclosure provides a method of measuring a true shear viscosity profile of a molding material in a capillary and a molding system performing the same. The method includes the operations of: determining a setpoint temperature of the molding material before injecting into the capillary; obtaining an initial shear viscosity profile at the setpoint temperature with respect to a shear rate of the molding material; fitting an initial temperature profile with respect to the shear rate according to the initial shear viscosity based on Cross William-Landel-Ferry model; fitting a first shear viscosity profile and a first temperature profile with respect to the shear rate according to the initial temperature profile based on the Cross-WLF model; and setting the first shear viscosity profile as the true shear viscosity profile when a difference between the first temperature profile and the initial temperature profile is not greater than a threshold.

A state determination device acquires data related to an injection molding machine, stores a learning model obtained by learning an operation state of the injection molding machine with respect to the data, and performs estimation using the learning model based on the data. Further, the state determination device acquires a correction coefficient, which is associated with a type of the injection molding machine and equipment attached to the injection molding machine and numerically converts and corrects the estimation result with a predetermined correction function to which the acquired correction coefficient is applied.