A diagnostic apparatus includes a context information acquisition unit that acquires context information of operation being performed from a plurality of mechanical apparatuses, a sensing information acquisition unit that acquires physical quantity sensing information sensed by each of sensing units of a target machine and other mechanical apparatuses, a sensing information separation unit that separates the physical quantity information of the target machine and the physical quantity information of the other mechanical apparatuses from each other based on the context information and the sensing information of each of the plurality of mechanical apparatuses, a feature information extraction unit that extracts feature information of the physical quantity information, and an anomaly determination unit that determines, from a model corresponding to the acquired context information and the extracted feature information, whether or not operation of the target machine is normal.

A numerical control system detects a state amount indicating a state of an injection operation of an injection molding machine, generates a characteristic amount that characterizes the state of the injection operation from the state amount, and infers an evaluation value of the state of the injection operation from the characteristic amount. The numerical control system detects an abnormal state on the basis of the evaluation value, generates or updates a learning model by machine learning that uses the characteristic amount, and stores the learning model in correlation with a combination of conditions of the injection operation.

A method and a system for estimating the state of wear of a cutting tool mounted on a machine tool. The system includes an acquisition module configured to acquire, for a determined duration of machining, values of an operating signal specific to the cutting tool mounted on the machine tool, and a microprocessor configured for calculating current values of a set of wear indicators from the values of the operating signal, and determining the state of wear of the cutting tool as a function of the current values of the set of indicators using a predetermined wear model modeling the state of wear of the cutting tool in function of learning values of the set of wear indicators.

A diagnostic apparatus includes a context information acquisition unit that acquires context information of operation being performed from a plurality of mechanical apparatuses, a sensing information acquisition unit that acquires physical quantity sensing information sensed by each of sensing units of a target machine and other mechanical apparatuses, a sensing information separation unit that separates the physical quantity information of the target machine and the physical quantity information of the other mechanical apparatuses from each other based on the context information and the sensing information of each of the plurality of mechanical apparatuses, a feature information extraction unit that extracts feature information of the physical quantity information, and an anomaly determination unit that determines, from a model corresponding to the acquired context information and the extracted feature information, whether or not operation of the target machine is normal.

A determination apparatus includes circuitry to receive operation information corresponding to an action being performed by a machine to be diagnosed and a detection signal of a physical quantity that changes according to the action of the machine; take out, from the detection signal, an operation detection signal indicating that the machine is operating, based on the operation information; extract feature information of the operation detection signal; select, from the feature information, particular feature information to be compared with a plurality of reference feature information; and determine a machining section of the machine in the feature information, based on the plurality of reference feature information and the particular feature information.

A device includes: a first acquiring unit to acquire context information corresponding to running operation among pieces of context information; a second acquiring unit to acquire detection information output from a detecting unit detecting a physical quantity of a target device; an extracting unit to extract, from the detection information, feature information indicating a feature of the detection information in an interval including a specific operation interval of the target device; a selecting unit to select reference feature information used as reference based on the feature information, and sequentially select pieces of target feature information; a calculating unit to calculate a likelihood of a process interval based on a comparison between the reference feature information and each piece of target feature information; a determining unit to determine whether the target feature information corresponding to the likelihood is included in the process interval based on the likelihood; and an estimating unit to estimate the process interval based on a determination result.

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.

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 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.

A numerical control system detects a state amount indicating a state of an injection operation of an injection molding machine, generates a characteristic amount that characterizes the state of the injection operation from the state amount, and infers an evaluation value of the state of the injection operation from the characteristic amount. The numerical control system detects an abnormal state on the basis of the evaluation value, generates or updates a learning model by machine learning that uses the characteristic amount, and stores the learning model in correlation with a combination of conditions of the injection operation.