A failure prediction device is provided with a machine learning device configured to learn the state of a brake of a motor with respect to data on the brake. The machine learning device observes brake operating state data indicative of an operating state of the brake when the brake is in a normal state, as state variables representative of a current environmental state, and uses the observed state variables to learn a distribution of the state variables with the brake in the normal state.

A numerical controller that collects data from an industrial machine and writes data into a storage medium includes: an interval setting unit that sets a time interval between cycles in which one cycle involves collection of operation information indicating an operating state of the industrial machine and writing of the collected operation information to the storage medium; a reduced service life calculation unit that calculates a service life of the number of writes of the storage medium reduced by the writing on the basis of the set time interval as a reduced service life; a determining unit that determines whether the calculated reduced service life exceeds a prescribed threshold; and a signal output unit that outputs a signal indicating that the reduced service life exceeds the prescribed threshold when it is determined that the reduced service life exceeds the prescribed threshold.

A numerical controller that collects data from an industrial machine and writes data into a storage medium includes: an interval setting unit that sets a time interval between cycles in which one cycle involves collection of operation information indicating an operating state of the industrial machine and writing of the collected operation information to the storage medium; a reduced service life calculation unit that calculates a service life of the number of writes of the storage medium reduced by the writing on the basis of the set time interval as a reduced service life; a determining unit that determines whether the calculated reduced service life exceeds a prescribed threshold; and a signal output unit that outputs a signal indicating that the reduced service life exceeds the prescribed threshold when it is determined that the reduced service life exceeds the prescribed threshold.

A selection support device that supports selection of a work machine to be used for work from among a plurality of work machines, the selection support device including: a history information acquisition unit configured to acquire history information on a use history of each work machine; a specifying unit configured to specify a degree of use of each work machine based on the history information; and a selection unit configured to preferentially select a work machine with a small degree of use as a work machine to be used for work.

A selection support device that supports selection of a work machine to be used for work from among a plurality of work machines, the selection support device including: a history information acquisition unit configured to acquire history information on a use history of each work machine; a specifying unit configured to specify a degree of use of each work machine based on the history information; and a selection unit configured to preferentially select a work machine with a small degree of use as a work machine to be used for work.

A prognostic and health management system for precision ball grinding machines includes: a detector connected to a first and a second grinding discs; and a central processing module including a determining unit, a historical data recording unit, a timing unit, and an alarm unit. The detector is connected to the determining unit, detects data of the two grinding discs, and sends the data to the determining unit, the determining unit compares data in the historical data recording unit to determine whether the first and second grinding discs are abnormal, if there is an abnormality, the alarm unit releases a warning signal, if the determining unit determines that there is no abnormality, the timing unit records a grinding time of the first and second grinding discs, and based on a comparison of the past records, the alarm unit releases a warning signal after a predetermined time has elapsed.

A prognostic and health management system for precision ball grinding machines includes: a detector connected to a first and a second grinding discs; and a central processing module including a determining unit, a historical data recording unit, a timing unit, and an alarm unit. The detector is connected to the determining unit, detects data of the two grinding discs, and sends the data to the determining unit, the determining unit compares data in the historical data recording unit to determine whether the first and second grinding discs are abnormal, if there is an abnormality, the alarm unit releases a warning signal, if the determining unit determines that there is no abnormality, the timing unit records a grinding time of the first and second grinding discs, and based on a comparison of the past records, the alarm unit releases a warning signal after a predetermined time has elapsed.

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 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 tool management system of a machine tool includes: a detection unit to detect at least one of vibration, acoustic waves produced during operation of the machine tool, and current value of a server motor of a driving machine tool; a tool replacement determination unit that determines the necessity to replace the tool on the basis of information related to a detection value of at least one of the vibration, the acoustic waves, and the current value detected during operation of the machine tool; and a detection start/end command setting unit that adds commands for a detection start point and a detection end point of at least one of the vibration, the acoustic waves, and the current value of the servo motor to a machining program.