A wire disconnection prediction device includes: a data acquisition part configured to acquire data relating to machining of a workpiece in a state where a wire is not disconnected during machining of the workpiece by a wire electric discharge machine; a preprocessing part configured to create, machining condition data of a condition relating to a machining condition commanded in machining of the workpiece, machining member data relating to a member used in the machining, and machining state data during machining of the workpiece, as state data indicating a state of the machining; and a learning part configured to generate, based on the state data created by the preprocessing part, a learning model indicating correlation between the state data and the state where the wire of the wire electric discharge machine is not disconnected.

An online prediction method of tool-electrode consumption adapted for an electrical discharge machining (EDM) apparatus includes an experimental design; extracting electrode consumption variables from machining parameters of the electrical discharge machining (EDM) apparatus; and obtaining a correlation between the machining parameters and the electrode consumption variables through a correlation analysis to obtain a prediction model capable of predicting an effective contact area of a tool-electrode and a workpiece. In addition, a prediction method of machining accuracy is provided.

A device for identifying a spark-erosion wire conditioned on a coil includes a radio tag, rigidly connected to the coil and accessible for reading data that it supports, identification data of the wire, supported by the radio tag, a data-reading device, associated with a wire spark-erosion machine, capable of reading the identification data supported by the radio tag of the coil, and capable of transmitting the identification data to the wire spark-erosion machine, an acquisition device for generating and recording over time as identification data, in the radio tag, historical data selected from the group that consists of historical usage data describing usage conditions of the wire supported by the coil and historical constraint data describing physical constraints to which the wire supported by the coil is subjected.

A wire disconnection prediction device includes: a data acquisition part configured to acquire data relating to machining of a workpiece in a state where a wire is not disconnected during machining of the workpiece by a wire electric discharge machine; a preprocessing part configured to create, machining condition data of a condition relating to a machining condition commanded in machining of the workpiece, machining member data relating to a member used in the machining, and machining state data during machining of the workpiece, as state data indicating a state of the machining; and a learning part configured to generate, based on the state data created by the preprocessing part, a learning model indicating correlation between the state data and the state where the wire of the wire electric discharge machine is not disconnected.

An online prediction method of tool-electrode consumption adapted for an electrical discharge machining (EDM) apparatus includes an experimental design; extracting electrode consumption variables from machining parameters of the electrical discharge machining (EDM) apparatus; and obtaining a correlation between the machining parameters and the electrode consumption variables through a correlation analysis to obtain a prediction model capable of predicting an effective contact area of a tool-electrode and a workpiece. In addition, a prediction method of machining accuracy is provided.

A method and a device for detection of metal and non-metal particle concentration of an electrical discharge machining liquid are disclosed. The method comprises steps of: (A) filling a tank with the electrical discharge machining liquid, wherein the tank comprises a tank wall, a first conductor, and a second conductor; (B) measuring a voltage between the first conductor and the second conductor by an electronic device, wherein the electronic device electrically connects to the first conductor and the second conductor, and the electronic device comprises a capacitance detection circuit; and (C) calculating a particle concentration or an equivalent dielectric constant of the electrical discharge machining liquid on the basis of the measured voltage.

A device for identifying a spark-erosion wire conditioned on a coil includes a radio tag, rigidly connected to the coil and accessible for reading data that it supports, identification data of the wire, supported by the radio tag, a data-reading device, associated with a wire spark-erosion machine, capable of reading the identification data supported by the radio tag of the coil, and capable of transmitting the identification data to the wire spark-erosion machine, an acquisition device for generating and recording over time as identification data, in the radio tag, historical data selected from the group that consists of historical usage data describing usage conditions of the wire supported by the coil and historical constraint data describing physical constraints to which the wire supported by the coil is subjected.