An abnormality-detecting device for detecting abnormalities of a tool of a machine tool comprises: an acquiring unit for acquiring multiple measured values relating to the tool as measurement data (vibration information, cutting force information, sound information, main shaft load, motor current, power value); a normal model unit for learning the measurement data acquired during normal machining by one class machine learning and creating a normal model; an abnormality-diagnosing unit for acquiring measurement data during machining after creation of the normal model while diagnosing whether said measurement data is normal or abnormal on the basis of the normal model; and a re-diagnosing unit for re-diagnosing measurement data, which has been diagnosed to be abnormal by the abnormality-diagnosing unit, by a method different from the abnormality-diagnosing unit.

An apparatus that includes a tool head; an insert that is coupled to the head and configured to engage an inner diameter of a workpiece, so as to machine the workpiece; a boring bar or drill tube coupled to the head, the boring bar or drill tube configured to extend through a guide bore in the workpiece; and a measuring device that is positioned proximate to the head and configured to measure a radial dimension, an axial dimension, or both of the inner diameter. The head may include a plurality of inserts, wherein the plurality of inserts are selectable such that the inserts are engageable with the inner diameter of the workpiece. The measuring device may include a contact-based measuring device.

A system for diagnosing performance degradation of a machine element includes an AE sensor that generates an AE waveform signal; a vibration sensor that generates an acceleration signal; a signal processing unit including an AE signal processing system that performs predetermined signal processing on the plurality of AE waveform signals, a vibration signal processing system that performs predetermined signal processing on the acceleration signal, and a switching parameter generating section that generates a predetermined numeric parameter to switch a measuring mode from the AE method to the vibration method; and controlling unit that selects a result of the processing in performed by the AE signal processing system at the initial stage and selects, after the numeric parameter successively turns from increasing to decreasing, a result of the processing by the vibration signal processing system.

A monitoring system for monitoring a plurality of components is provided. The monitoring system includes a plurality of client systems. The plurality of client systems is configured to generate a plurality of component status reports. The plurality of component status reports is associated with the plurality of components. The monitoring system also includes a component wear monitoring (CWM) computer device configured to receive the plurality of component status reports from the plurality of client systems, generate component status information based on a plurality of component status reports, aggregate the component status information to identify a plurality of images associated with a first component, and compare the plurality of images associated with the first component. The plurality of images represents the first component at different points in time. The CWM computer device is also configured to determine a state of the first component based on the comparison.

A diagnostic device includes a reception unit and a determination unit. The reception unit is configured to receive context information and sensing information. The context information corresponds to a certain operation of a target item that constitutes a target device. The context information is a piece of a plurality of pieces of context information each describing an operation of the target item determined depending on a type of operation of the target device. The sensing information is on a physical quantity that varies in accordance with the operation of the target item. The determination unit is configured to determine a state of the target item based on the sensing information detected while the target item is performing the certain operation, and based on a model corresponding to the received context information. The model is a model of one or more models respectively defined for one or more pieces of the context information.

A mist removal system includes an observation unit that observes a situation related to the mist concentration in a factory, a first mist countermeasure unit that reduces the mist concentration in a machine tool, a second mist countermeasure unit that reduces the mist concentration in the factory, and a control unit. The control unit controls observation by the observation unit and interlocking operation of the first mist countermeasure unit and the second mist countermeasure unit. Furthermore, the control unit determines the control details of interlocking operation of the first and second mist countermeasure units based on the observation results of the mist concentration obtained by the observation unit.

A broken tool detection mechanism applied in a CNC machine includes a base support, a first conductive elastic sheet securely mounted on the base support, and a second conductive elastic sheet. The second conductive elastic sheet is mounted on the base support, at least partially located over the first conductive elastic sheet, and spaced apart from the second conductive elastic sheet by a predetermined distance. The second conductive elastic sheet is pushed towards the first conductive elastic sheet so that the first conductive elastic sheet and the second conductive elastic sheet make electrical contact.

A mist removal system includes an observation unit that observes a situation related to the mist concentration in a factory, a first mist countermeasure unit that reduces the mist concentration in a machine tool, a second mist countermeasure unit that reduces the mist concentration in the factory, and a control unit. The control unit controls observation by the observation unit and interlocking operation of the first mist countermeasure unit and the second mist countermeasure unit. Furthermore, the control unit determines the control details of interlocking operation of the first and second mist countermeasure units based on the observation results of the mist concentration obtained by the observation unit.

A monitoring system for monitoring a plurality of components is provided. The monitoring system includes a plurality of client systems. The plurality of client systems is configured to generate a plurality of component status reports. The plurality of component status reports is associated with the plurality of components. The monitoring system also includes a component wear monitoring (CWM) computer device configured to receive the plurality of component status reports from the plurality of client systems, generate component status information based on a plurality of component status reports, aggregate the component status information to identify a plurality of images associated with a first component, and compare the plurality of images associated with the first component. The plurality of images represents the first component at different points in time. The CWM computer device is also configured to determine a state of the first component based on the comparison.

The present invention relates to a control device 200 for use on a numerically controlled machine tool 100, comprising a machine control unit 230 for controlling actuators of the machine tool for a machining process for a workpiece to be performed on the machine tool 100, in particular on the basis of control data, and a monitoring unit 250 for monitoring an operating state of the machine tool 100. In accordance with the invention, the monitoring unit 250 has a computer-implemented neural network 253 (NN), which in particular is designed to read input data from the machine control unit 230 and to output output data specifying an operating state of the machine tool 100.