A system for improving drill bit performance, having processors and memory storing instructions to obtain a wear report for a drill bit, wherein the wear report includes wear characteristics of the drill bit and drill operating parameters under which the drill bit was used; compare the wear characteristics of the drill bit to a threshold for acceptable drill bit wear; and adjust drill operating parameters based on the wear characteristics of the drill bit. The instructions to obtain the wear report for the drill bit include instructions to analyze images of the drill bit to identify wear characteristics; identify wear patterns based on the wear characteristics of the drill bit; identify probable drilling conditions based on the wear patterns; and generate the wear report for the drill bit based on the images of the drill bit, the wear characteristics of the drill bit, and the probable drilling conditions.

An on-machine monitoring system for the failure state of the rotating tool and a detection method thereof are provided. The monitoring system includes a detector, a data processing controller, a tool data server, and a Hall current sensor. A tool diameter and a tool length are determined according to image sequences of a tool. A wear state and a breakage state of the tool are determined according to the tool diameter and the tool length. A spindle current signal is acquired by the Hall current sensor. And an edge chipping state and a breaking state of the tool are determined according to the spindle current signal.

The disclosure provides a method to estimate tool life on a cutting machine. A sensor is installed on the cutting machine to measure the cutting thrust of a cutting tool during operation. Specifically, the information gathered from the sensor enables the cutting tool to cut a workpiece at different settings of cutting rate, with a maximum cutting thrust of the cutting tool measured during each cut, and defined as a characteristic signal. Through the characteristic signals obtained from the multiple cuts, factorization processing and inverse processing are initiated to obtain plural values in a complex remaining life index for the cutting tool. Using the cutting rate as the horizontal axis and the remaining life as the vertical axis, the complex remaining life and corresponding cutting rates are plotted on the vertical axis and the horizontal axis to form a line graph illustrating the complex remaining life index.

The wear status of a micro-endmill tool may be inferred by monitoring the chip production rate of the tool in operation. Chips may be extracted from a work area, captured on an adhesive surface, imaged, and counted to determine the chip production rate. When the rate of chip production falls, the feed rate of the micro-endmill may be increased to a level suitable for the current state of tool wear. In this manner, costly and inconvenient work stoppages to evaluate the wear status of a tool are eliminated.

A tool diagnostic device includes a data acquisition unit configured to acquire, as waveform data, a state quantity of a motor for driving a tool before and after rotation of the tool stops in tapping, a reference waveform generation unit configured to generate reference waveform data, a difference waveform calculation unit configured to calculate, as difference waveform data, a difference between waveform data and the reference waveform data, a waveform feature calculation unit configured to calculate waveform feature data indicating a feature of a waveform from the difference waveform data, a learning result storage unit configured to store a learning result of learning a correlation between waveform feature data and a tool life, and a state diagnostic unit configured to diagnose a state of the tool based on the waveform feature data using a learning result.

An information processing apparatus acquires detection information of a physical quantity that changes according to an operation state of a target device, transmits an acquisition request to the target device at predetermined time, to acquire context information relating to an operation status of the target device in response to the acquisition request, specifies a processing period in which the target device is in the middle of processing of the target object based on the predetermined time and the context information, extracts processing period detection information of the specified processing period from the detection information, and determines an occurrence of a defect relating to processing by the target device during the processing period based on the processing period detection information and the context information used for specifying the processing period.

A method for determining part wear, such as using a wear model, includes receiving, from a sensor, sensor data representing a surface of a wear part. The method further includes determining an estimated time until the part should be replaced. The method further includes batching together multiple wear parts that need replacing to enable a user to replace multiple parts in one maintenance period. The method may also include providing information to the user during replacement of a worn part to indicate the part location.

A computer-implemented method determines a property of a machine, in particular a machine tool, without metrologically capturing the property. The method includes the following steps: capturing one or more first time series of one or more physical measurement variables of the machine; detecting change points in the one or more first time series; extracting pattern-sequence instances from the first time series on the basis of the detected change points; producing a plurality of pattern-sequence classes in accordance with the extracted pattern-sequence instances; identifying at least one characteristic of a plurality of pattern-sequence instances of the same pattern-sequence class and a time curve of the characteristic; determining a property of a machine using the determined characteristic and/or using the time curve of the determined characteristic.

An apparatus for detecting the status of a tool in a machine tool may include: a sensor unit configured to sense acceleration of a spindle of the machine tool in an x-axis direction and a y-axis direction during processing; and a processing device configured to convert the x-axis signal and the y-axis signal, sensed by the sensor unit, into signals capable of representing a cutting force by processing the x-axis and y-axis signals, detect a resultant force, and plot the detected resultant force on a polar coordinate system.

A method of controlling a machine tool comprising the steps of: providing a data memory containing, for at least one specific working axis of the plurality of working axes, a plurality of data tuples each assigning a load value to a position value relative to the specific working axis, selecting a first data tuple and a second data tuple whose load values are different, and generating at least one control command for the machine tool, wherein the control command is adapted to perform a first tolerance measurement at a first position value and a second tolerance measurement at a second position value, and wherein, based on a first result of the first tolerance measurement and a second result of the second tolerance measurement, information about wear of a part of the machine tool is output. A corresponding device is also be disclosed.