A first diamond layer made of polycrystalline diamonds and doped with foreign atoms, is arranged on a metal surface of a machining tool, and is used to detect the degree of wear of an undoped polycrystalline second diamond layer, which is arranged on the doped diamond layer and forms a functional region of the machining tool, wherein at least one physical parameter is detected continuously or periodically during operation of the tool, and wherein a change in the parameter indicates the degree of wear of the undoped second diamond layer. The doped diamond layer forms an “intelligent stop layer” for the tool because as a result of change in the transition from the undoped to the doped layer, the conductivity of the system changes, for example, and this change can be used to form a stop signal for the machine drive before the tool and the machined workpiece are damaged.

A method, system and computer-usable medium are disclosed for monitoring and controlling a machining process of parts. Data as to dimensions of produced parts are gathered during a production process. The parts are produced based on part control plan. The data of the dimensions are plotted as to statistical information related to a distribution curve. Determination is made if a trend in the dimensional data approaches an upper control limit and a lower control limit. Corrective action is taken if the trend approaches either the upper control limit or the lower control limit.

A method includes measuring raw sensor information of a tool over a period of time with a sensor tag coupled to an external surface of the tool. The method also includes determining one or more events of the tool based on the raw sensor information and calculating an aggregate time for each type of event from the one or more events determined over the period of time. The method also includes wirelessly transmitting a history of the one or more events from the sensor tag to a remote computing device. The history comprises the aggregate time for each type of event from the one or more types of events over the period of time.

Tool bodies, tools and machines for operating the tool include electronic circuits for providing data, collecting data, analyzing data and for controlling machines based on such data. Tool bodies and tools may include electronic circuits having data collecting sensors, which may be embedded in a housing with the electronic circuit and/or positioned outside of such a housing. Sensors include temperature sensors, motion sensors, strain sensors, moisture sensors, electrical resistance sensors, position sensors, antennas, and other components.

A method is provided for assessing wear of a drill bit throughout its use for carrying out the drilling of elements to be drilled constituted by at least one layer and at least one material. The wear of the drill bit expresses its capacity to perform a drilling that meets at least one criterion of quality of a drilling. The method includes at least: measuring or detecting at least one parameter having an effect on the wear of the drill bit, the parameter being chosen from: the depth of drilling performed by the drill bit, and the entry of the drill bit into the element to be drilled; and determining at least one state of wear of the drill bit, each state of wear being determined as a function of one of the parameters and being characteristic of one of the criteria of quality of a drilling.

A method for detecting at least one tool state of a tool of a machine tool for machining workpieces, which includes at least one tool holder, at least one positioning drive, which includes at least one tool which is arrangeable or arranged rotationally fixed in the tool holder and which includes at least one control unit. The method includes the following steps: detecting or providing tool and/or workpiece data in the storage means and/or the control unit; providing at least one reference drive frequency of the rotary drive and/or the positioning drive; detecting at least one ACTUAL driving frequency of the rotary drive and/or the positioning drive; assigning the ACTUAL drive frequency of a reference drive frequency of the rotary drive and/or the positioning drive by the control unit and evaluating and/or interpreting at least the reference drive frequency associated with the ACTUAL drive frequency by the control unit.

A machine tool includes a tool main spindle device to execute machining of a first system in a first workpiece main spindle device for rotationally holding a workpiece and machining of a second system in a second workpiece main spindle device for rotationally holding the workpiece by an exchangeable main spindle head tool. Drive control of each device is performed by a control device, the control device including a tool management processing section to calculate a total usage time of the main spindle head tool based on the machining of the first system or the machining of the second system executed in the tool main spindle device, to store the calculated total usage time as first tool management data or second tool management data, and to rewrite the same total usage time in the other of the second tool management data or the first tool management data.

Provided is a prediction device, to which one or more wire electrical discharge machines are connected, the one or more wire electrical discharge machines each performing machining on an object to be machined according to a predetermined machining condition while moving a wire electrode relatively with respect to the object to be machined along a machining path, the prediction device including a prediction unit that predicts, for a predetermined component constituting the wire electrical discharge machine, a predicted rate of consumption indicative of a rate of consumption based on the machining condition when the wire electrode is moved relatively by a unit distance, and a display unit that displays the predicted rate of consumption of the component.

A machine tool includes: a spindle that allows a tool to be detachably mounted thereon; a tool changing device that holds a plurality of the tools, and attaches and detaches any of the tools to and from the spindle; a date and time storage unit that stores date and time when operation of the spindle is stopped last; and a calculation unit that calculates unused time of the spindle on the basis of the date and time stored in the date and time storage unit, when the tool is to be detached from the spindle, wherein in a case where the unused time calculated by the calculation unit is longer than a predetermined threshold value, the tool changing device performs detaching motion of the tool from the spindle for longer time compared to a case where the calculated unused time is at or less than the threshold value.

A self-aware machine platform is implemented through analyzing operational data of machining tools to achieve machine tool damage assessment, prediction and planning in manufacturing shop floor. Machining processes are first identified by matching similar processes through an ICP algorithm. Machining processes are further clustered by Hotelling's T-squared statistics. Degradation of the machining tool is detected through a trend of the operational data within a cluster of machining processes by a monotonicity test, and the remaining useful life of the machining tool is predicted through a particle filter by extrapolating the trend under a first-order Markov process. In addition, process anomalies across machines are detected through a combination of outlier detection methods including SOMs, multivariate regression, and robust Mahalanobis distance. Warnings and recommendations are flexibly provided to manufacturing shop floor based on policy choice.