A wire electrical discharge machine includes: a wire electrode cumulative moving time calculator for calculating a value correlated to a wire electrode cumulative moving time as a cumulative value of time for which a wire electrode has moved in each of multiple wire electrode moving regions which are defined by dividing a movable range of the wire electrode moving relative to a worktable; and a display control unit for displaying on a display unit the information on values correlated to the wire electrode cumulative moving time for respective wire electrode moving regions.

A numerical controller acquires state information (machine condition) such as the current temperature of a drive unit to determine whether a machining operation based on a machining program can be started or not by comparing the state information with a machine condition history recorded in a recording unit. If determined that the machining operation can be started, a machining operation start command is output and if determined that the machining operation cannot be started, the machine condition is monitored to withhold outputting of the machining operation start command until the machine condition allowing to start the machining operation based on the machining program appears.

The disclosure relates to a tool part for a cutting tool having an identification marker arranged at the tool part, wherein the identification marker is a unique machine readable code associated with individual dimension information data. The individual dimension information data includes at least one individually measured dimension of the tool part as measured when manufacturing the tool part that will change while wearing the tool part. The disclosure further relates to a system, a method and computer program product for utilizing an identification marker on a tool part for a cutting tool, for determining a tool wear of the tool part.

A machine learning device for performing machine learning with respect to a numerical control device which causes a machine tool to operate, and is provided with: a state information acquisition unit that causes the machine tool to perform cutting work, in which a cutting amount and a cutting rate are set, and acquires state information including the cutting amount and cutting rate; an action information output unit that outputs action information; a reward calculation unit that acquires determination information that is information about the strength of pressure applied to a tool at least during cutting work, the shape of the waveform of the pressure applied to the tool, and time it has taken to perform work, and outputs a reward value in reinforcement learning; and a value function update unit that updates a value function on the basis of the reward value, the state information, and the action information.

A wear prognosis method and a maintenance method for an earth working machine are disclosed, along with an apparatus for performing the method. Provision is made that the current wear state of one or more earth working tools is sensed. The residual wear capacity until the wear limit is reached is then ascertained from the current wear state.

An analysis device according to the present disclosure analyzes the state of a machining tool. The analysis device includes: an acquisition unit that acquires a measurement result from at least one sensor fitted to the machining tool; a computation unit that performs data processing to the measurement result acquired by the acquisition unit; and an image processing unit that displays a first image and a second image on a display screen, the first image displaying the measurement result acquired by the acquisition unit in time-series, the second image displaying a computation result after the data processing is performed by the computation unit. The image processing unit displays, as the second image, the computation result corresponding to the measurement result for a specific time period in the first image.

A machining state diagnosis apparatus (10) includes a machining state information estimation device (1), a learning information storage (11) storing information on relationship between estimated machining state information and actual machining state information, and a machining state diagnosis unit (12) diagnosing a machining state in actual machining using control information, based on machining state information obtained during the actual machining, machining state information estimated based on corresponding control information by the machining state information estimation device (1), and the relationship information stored in the learning information storage 11. The machining state information estimation device (1) includes an information storage (2) storing the control information and information on a workpiece and a tool, a machining state information estimator (3) estimating machining state information in relatively moving the workpiece and the tool, based on the information on the workpiece and the tool and the control information, and an image data generator (4) generating image data based on the estimated machining state information.

The disclosure provides a method for manufacturing an ophthalmic device, comprising machining to provide a predetermined surface on a part and which corresponds to an initial ophthalmic surface, the machining comprising: selecting (130) a machining tool having a cutting edge; selecting (140) the initial ophthalmic surface of the ophthalmic device intended to be manufactured; providing (150) a determined kinematics of the machining tool which is function of the initial ophthalmic surface and of a wear parameter of the cutting edge; machining (160) the predetermined surface according to the determined kinematics of the machining tool; wherein the wear parameter is function of at least a distance travelled by the cutting edge for machining the predetermined surface and/or a friction time between the cutting edge and the part which is machined.

A method for monitoring the condition of a hard finishing machine, in particular a grinding machine, wherein the hard finishing machine has a number of NC-controlled axes which are actuated during the machining of a workpiece, wherein, for the purpose of evaluating the condition of the hard finishing machine, at least one reference run is performed on at least one axis, during which the response of the axis to a drive signal is measured and evaluated. In order to enable improved condition monitoring of the hard finishing machine, the reference run includes a phase in which the axis is accelerated and/or braked.