A tool post of a machine tool, in which the tool post is capable of receiving a cutting insert for machining a component, is provided. The tool post includes at least one sensor capable of determining a parameter representative of a cutting action between a component to be machined and a cutting insert; and a support housing which is electrically connected to the sensor and includes a battery and a printed circuit board supplied with current by the battery. The printed circuit board supports, at least partially, a radio transmission unit. The housing includes a base and a cover which can be detached from one another. The battery is supported by the cover and the printed circuit board by the base or vice versa.

A fixture for a thin-walled workpiece includes two clamping devices. Each of the clamping devices has a metal carrier and a damper. The metal carrier has a carrying portion and a supporting portion, where the supporting portion has a stair portion having a plane surface and a standing surface with a slope. The damper has a metal clamping portion and a damping portion. One end of the metal clamping portion is formed as an inclined surface. The damping portion has at least two elastic layers and at least one metal layer, which are laminated in an interlacing arrangement with the same slope of the inclined surface. One of the elastic layers is disposed to connect the inclined surface. The end of the metal clamping portion connecting the elastic layer is located on the stair portion, while the opposite end of the metal clamping portion protrudes out of the supporting portion.

A machine tool comprises a measuring device, which is arranged on the machine tool, a control device, and a tool unit. The measuring device comprises at least one structure-borne sound sensor. T control device is coupled to the measuring device and to the tool unit. The control device is configured to acquire, by means of the measuring device, structure-borne sound signals caused by the machine tool and to determine a state variable, which describes an actual state of the machine tool, by forming a differential spectrum from a broadband reference spectrum and a broadband actual spectrum.

An abnormality factor identification apparatus includes a sensor signal obtaining unit that obtains sensor signals associated with the physical state of a machine, an operating state determination unit that determines operating states of the machine based on information obtained from the machine, an abnormality level calculation unit that calculates the abnormality levels of the sensor signals for each operating state of the machine determined by the operating state determination unit, and a factor identification unit that determines a factor in an abnormality in the machine from historical data being a series of the abnormality levels for each operating state.

A machine tool includes a workpiece spindle device which rotates a workpiece, a tool post which can move a tool in a first axis direction (X-axis direction) which is a radial direction of the workpiece and a second axis direction (Z-axis direction) which is an axial direction of the workpiece, and an articulated robot including a plurality of arms, a plurality of joints, and end effectors. The plurality of joints connect the plurality of arms in a rotatable manner around an axis parallel to a third axis (Y-axis) orthogonal to the first axis and the second axis, and the end effectors move in a plane parallel to a movement plane of the tool.

A method for facilitating analysis of causes of machining defects is provided. The method is carried out by a computer system. The method includes the step of obtaining motion data and vibration acceleration data about the tip of a cutter mounted on a machine tool. The method further includes the step of obtaining time-frequency information about the vibration acceleration data by performing a time-frequency analysis on the vibration acceleration data. The method further includes the step of obtaining vibration-displacement data by normalizing the time-frequency information. The method further includes the step of obtaining amplitude-distribution data about the tip by synchronizing the motion data and the vibration-displacement data.

In the disclosure, a failure of a device performing work while moving is more reliably detected while the data amount of failure diagnosis data is reduced. The disclosure includes a frequency analyzing part which performs a frequency analysis on acquired data from an acceleration sensor; a maximum frequency detecting part which detects a maximum frequency from a result of the frequency analysis; and a failure diagnosis data generating part which sets a frequency twice or more of the maximum frequency as a sampling frequency, samples the acquired data from the acceleration sensor, and generates the failure diagnosis data.

A method for automated condition monitoring whereby techniques of automated vibration analysis and signal processing are combined with deep learning/machine learning techniques for an enhanced system of automated anomaly detection, problem classification, and problem regression. The method may be implemented in software, firmware or hardware to run autonomously. Machines monitored and analyzed according to the disclosed method are typically found in industrial plants or commercial applications, but the disclosed invention may be applied to any rotating equipment such as motors, fans, pumps, compressors, and etc., in any environment where they are functioning.

A machining unit for a program-controlled machine tool. In particular, a spindle device for a program-controlled machine tool including a spindle housing; a working spindle which is mounted in the spindle housing in a rotatable manner about a spindle axis and which includes a clamping device for clamping a tool interface that is inserted in a tool receiving section of the spindle device and is configured to hold a milling or boring tool; and a sensor device which is arranged on the spindle housing and which includes at least one structure-borne sound sensor configured to detect structure-borne sounds or vibrations occurring during grinding operations.

Disclosed is an artificial tooth machining apparatus which protects a workpiece and first and second tools from heat and frictional contact that may occur when the workpiece is machined and enhancing machining precision by supplying water or air to the tools by a supply unit, a first nozzle portion, and a second nozzle portion, which has a lifespan lengthened by preventing chips of the workpiece or water or air from being introduced to a mechanism operation part of a base part by a discharge unit and a blocking unit, and which prevents a collision between the first tool and the second tool during machining of the workpiece by a tool collision preventing controller.