The present disclosure relates to attachable monitoring devices for molding tools. One example embodiment includes a method. The method includes receiving, by a first computing device and from a monitoring device that includes a plurality of sensors, a plurality of sensor readings associated with operation of an injection press or with a mold usable by the injection press. The plurality of sensor readings were collected by the monitoring device when the monitoring device was attached to an exterior of the mold. The method also includes determining, by the first computing device, one or more metrics associated with a state of the injection press or a state of the mold. Determining the one or more metrics includes applying a machine-learned model to the plurality of sensor readings. Further, the method includes providing, by the first computing device to a second computing device, the one or more metrics.

An abnormality detection apparatus for detecting an abnormality of a ball screw provided in an injection molding machine includes a current sensor configured to detect an alternating current of a motor for applying a driving force to the ball screw; and a computation unit configured to detect an abnormality of the ball screw based on information related to a distribution of frequency components obtained by frequency analysis of an alternating current detected by the current sensor, and information related to a distribution of frequency components obtained by frequency analysis of an alternating current detected when the ball screw, which is normal, operates.

An ultrasonic inspection system determines whether or not a thermally conductive resin forming a thermally conductive resin layer is filled through a waveform change of an ultrasonic wave measured by transmitting the ultrasonic wave toward a portion of an edge of a bottom surface of a module frame from the outside. An ultrasonic sensor at one of two opposite edges of an exterior surface of the bottom surface of the module frame determine a height of the resin within the battery module.

A silicone pencil preparation device includes: a conveying apparatus, a grabbing apparatus, a silicone injection molding machine and a control apparatus. The conveying apparatus includes an unprocessed pencil conveying apparatus and a processed pencil conveying apparatus. The silicone injection molding machine includes a main machine provided with a mold and a mold closing system, the mold includes a front mold and a rear mold, the mold is secured onto the mold closing system, and a middle portion of a front mold cavity is provided with a pencil carrying slot. The control apparatus is configured to perform the following steps: moving an unprocessed pencil to the pencil carrying slot; performing a mold closing operation; performing an injection molding operation on the front mold cavity and a rear mold cavity; performing a mold splitting operation; and moving a processed pencil in the pencil carrying slot to the processed pencil conveying apparatus.

A plurality of AE sensors 6r, 6f are provided on a heating cylinder 2 at a plurality of different positions Xr, Xf in a forward-rearward direction Fs so as to detect AE waves AE waves We. Position data Dx related to a position where each AE wave We is generated are obtained on the basis of arrival times Tr, Tf of the AE wave We obtained from the AE sensors 6r, 6f. For each combination of a predetermined sampling period Tp and a predetermined set of the position data Dx, the number of times AE wave signals Sfe, etc. related to the generated AE wave We have exceeded a threshold value L set beforehand is obtained as attack number data Da. The number of AE wave signal components Sp having exceeded a threshold value set beforehand is obtained as event count data De. At least a generation pattern Ps of sets of the attack number data Da and sets of the event count data De which correspond to sets of the position data Dx is graphically displayed.

A controller of an injection molding machine includes a detection part configured to detect whether or not a process in each process performed in the injection molding machine has started based on preset conditions in the process, and an output part configured to output waveform information representing a change of a performance value detected in the process or a subsequent process that is subsequent to the process when the detection part detects that the process has started.

A setting timing data acquisition module configured to acquire a plurality of pieces of setting timing data being monitoring data at preset timings among pieces of monitoring data obtained when molding a molded article by an injection molding machine; a waveform data acquisition module configured to acquire waveform data being the monitoring data continuous in a predetermined period among the pieces of monitoring data; a sample point data acquisition module configured to acquire a plurality of pieces of sample point data in the waveform data; a combined data generation module configured to combine a monitoring data group including the plurality of pieces of setting timing data and the plurality of pieces of sample point data to generate combined data; and a pass/fail determination module configured to determine whether a defective article has occurred in the molded article, based on the combined data are included.

A hot runner process controller configured to monitor the status and operation of a hot runner system to autonomously generate information to improve the quality of injection molding process of a hot runner system having an inlet nozzle, one or more manifolds and one or more nozzles with actuator or without actuator, and one or more heating elements, the hot runner process controller is self-operating, and independent from the injection molding machine, includes: one or more sensors located on, in or at the hot runner system to detect the status and/or the operation of the hot runner system, and a processing unit and a memory. The processing unit is connected to the one or more sensors, wherein the memory stores data and program codes. The processing unit is configured to load and execute the program code to compare sensor information with the stored data and to determine if the hot runner system is in an operable status, and in case the hot runner system is in an operable status, configured to generate status information to activate the one or more heating elements and/or the one or more actuators enabling a production operation of the injection molding machine. In case the hot runner system is not in an operable status, configured to generate status information to deactivate the one or more heating elements and/or close or deactivate the one or more actuators disabling a production operation of the injection molding machine.

The present disclosure relates to attachable monitoring devices for molding tools. One example embodiment includes a method. The method includes receiving, by a first computing device and from a monitoring device that includes a plurality of sensors, a plurality of sensor readings associated with operation of an injection press or with a mold usable by the injection press. The plurality of sensor readings were collected by the monitoring device when the monitoring device was attached to an exterior of the mold. The method also includes determining, by the first computing device, one or more metrics associated with a state of the injection press or a state of the mold. Determining the one or more metrics includes applying a machine-learned model to the plurality of sensor readings. Further, the method includes providing, by the first computing device to a second computing device, the one or more metrics.

A method for operating a hydraulic system of an industrial machine, which hydraulic system comprises an actuator and a hydraulic pump which are connected fluidically via a hydraulic line which is assigned a pressure sensor. The hydraulic pump comprises an electric motor and a pump head driven by the latter. A pressure within the hydraulic line is measured via the pressure sensor, and a first pressure value is generated therefrom. A second pressure value is determined on the basis of operating data of the electric motor and a theoretical model. A fault is detected if the first pressure value differs from the second pressure value by more than a tolerance value. An industrial machine is also provided.