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 for manufacturing a wind turbine blade, including the step of monitoring a process of infusing and/or curing a fiber lay-up with resin in a mold, wherein the monitoring is based on sensor data obtained from the resin infusion and/or curing process displayed in an augmented reality device, is provided. Displaying sensor data obtained from the resin infusion and/or curing process in an augmented reality device allows to better monitor the resin infusion and/or curing process. Thus, the quality of the manufactured wind turbine blade can be improved.

An artificial intelligence-based injection molding system in which molding conditions can be changed to manufacture fair-quality products when defective products are manufactured because of disturbances during the injection molding including an injection molding machine which performs injection molding by injecting a molding material into a mold; an injection state data acquisition unit for acquiring, during injection molding, current injection state data that includes the viscosity profile of the molding material injected into the mold and/or the injection pressure value thereof; a determination unit, which inputs the current injection state data into a molding quality maintenance model trained with predetermined target injection state data, so as to determine whether to maintain molding quality; and a molding condition setting unit for changing a preset molding condition so that the current injection state data follows the target injection state data, when the determination unit determines not to maintain the molding quality.

An injection molding machine includes a cylinder that accommodates a molten resin, a discharging nozzle, a piston that discharges the molten resin from the discharging nozzle, and one or more processors configured to execute the following functions. The functions include calculating a target pressure at which a flow rate of the molten resin discharged from the discharging nozzle becomes an indicated flow rate, controlling a pressure of the molten resin in the cylinder such that the pressure becomes the target pressure, acquiring a temperature of the molten resin in the cylinder, and acquiring a pseudo-plastic viscosity corresponding to the temperature of the molten resin. The target pressure is calculated based on the indicated flow rate, the temperature of the molten resin, the pseudo-plastic viscosity, and the size of the discharging nozzle.

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.

The present invention provides a molding machine that can easily detect viscosity of resin in a cylinder without advance preparations. An injection molding machine (10) includes an ultrasonic viscosity sensor (20), and the ultrasonic viscosity sensor (20) includes an ultrasonic vibration portion in contact with resin filled in a cylinder (12).

The invention relates to a method for the online sensing of the rheology of thermoplastic and/or elastomer material for the production of injection-molded parts, wherein a measuring tool (6) is arranged in an injection-molding machine (1) between the stationary clamping plate (2) and the movable clamping plate (3) thereof instead of a mold die, wherein the measuring tool (6) comprises a measuring channel (13), in the course of which at least two pressure sensors (16) and at least two temperature sensors (17) are arranged, which transfer corresponding measured values of the material injected by means of an injection assembly (5) into the measuring channel (13) to a programmable logic controller (PLC) belonging to the injection-molding machine (1), with these measured values being processed by means of an algorithm in the PLC, evaluated and made available for the actual injection process.

A method for determining optimized shape data representing a shape of a molded workpiece formed from a molded material or/and a mold cavity of a molding tool, wherein the molded material hardens depending on at least one solidification parameter, the method including: a) providing shape data representing a shape of the workpiece or/and cavity, b) providing material data representing the molded material, c) providing molding process data representing the molding process, d) providing tool data representing the tool embodying the cavity, e) determining predictive shape data based on initial model data comprising the at least one solidification parameter and data provided in steps a), b), c), and d) simulating the molding process, f) generating optimized predictive shape data as the optimized shape data based on at least predictive shape data determined in step e) and based on first initial AI data comprising the at least one solidification parameter and data provided in steps a, b), c), and d), by means of an artificial neural simulation optimization network trained to optimize predictive shape 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.

Apparatus and methods for forming and printing hollow bodies from amorphous materials to form three-dimensional objects are provided. Apparatus provide a hollow body forming and printing machine, and methods for determining a desired amount of impact deformation for the hollow spheres, including calculating specific characteristics of the hollow spheres and the amorphous material, deriving a target viscosity range, adjusting the apparatus to satisfy the target viscosity range, and using the apparatus to form a plurality of hollow spheres with controlled deformation.