In a method for monitoring an operating behavior of a tool holder, a resultant measurement axis signal is calculated using at least two measurement axis signals of at least two radially oriented measurement axes of a sensor provided in the tool holder. The monitoring is performed using the resultant measurement axis signal or the resultant.

A polishing system performs chemical-mechanical polishing of an object to be polished using an abrasive slurry. The polishing system includes a polishing amount calculator that measures an amount of free metal ions of a metallic element derived from the object to be polished in a processed slurry and calculates a polishing amount of the object to be polished from the amount of the free metal ions. The object to be polished is a glass containing the metallic element of Group 1 or Group 2 of a periodic table.

The self-propelled construction machine according to the invention, in particular road-milling machine, recycler, stabiliser or surface miner, comprises a machine frame 2, which is supported by a chassis 1, which has wheels or tracks 1A, 1B. A milling drum 4 is arranged on the machine frame. The wheels or tracks 1A, 1B and the milling drum 4 are driven by a drive unit 8. Furthermore, the construction machine comprises a control unit 19 for controlling the drive unit 8 and a signal-receiving unit 18 for detecting at least one measurement variable M(t) which is characteristic of an operating state of the milling drum 4. The construction machine is characterised in that the rotational speed of the milling drum 4 is adapted, on the basis of at least one measurement variable M(t) which is characteristic of a critical operating state of the milling drum, to the operating conditions of the construction machine in such a way that the milling drum is operated in a non-critical operating state. The adaptive open-loop control of the milling drum rotational speed allows the construction machine to be operated at an optimum operating point with respect to the milling drum rotational speed.

A system and method for monitoring and predicting wear of a cutting tool used for machining a workpiece is disclosed. The system includes a cutting tool having a shank and a cutting head. The system also includes a split, modular and wireless wear detection system including one or more sensors mounted to the cutting tool for providing a data signal representative of a physical condition of the system, and a data recording and data transmitting device for recording the data signal from the one or more sensors and for generating and transmitting a data signal to a processor. The processor applies a machine learning data processing technique in real time to monitor and/or predict a condition of various components and/or parameters of the system during a metal cutting operation.

A machine tool includes a workpiece spindle device which rotates a workpiece, a tool post which can move a tool in a first axis direction (X-axis direction) which is a radial direction of the workpiece and a second axis direction (Z-axis direction) which is an axial direction of the workpiece, and an articulated robot including a plurality of arms, a plurality of joints, and end effectors. The plurality of joints connect the plurality of arms in a rotatable manner around an axis parallel to a third axis (Y-axis) orthogonal to the first axis and the second axis, and the end effectors move in a plane parallel to a movement plane of the tool.

A turning tool includes a power receiving coil, a sensor, and a wireless unit. The power receiving coil receives power transmitted from a power transmitting coil in a non-contact manner. The sensor is electrically connected to the power receiving coil. The wireless unit transmits data detected by the sensor to an outside.

A system for acceleration adjustment of machine tool at rapid traverse includes a signal measurement module, a signal judgment module and an acceleration optimization module. The machine tool has a servo motor and a working platform. The signal measurement module measures signals while the servo motor drives the working platform from a first specific position to a second specific position, or from the second specific position back to the first specific position. The signal judgment module judges whether the actual maximum current value of the motor is equal to the manufacturer's specification according to the signals; and if negative, the acceleration optimization module calculates and optimizes an axial acceleration till an optimal value is achieved. Then, a curve smoothing time of the optimal acceleration is calculated and optimized by the acceleration optimization module. In addition, a method for acceleration adjustment of machine tool at rapid traverse is provided.

A workpiece machining device for executing machining of a workpiece using a machining tool, including a detection section configured to detect a detectable physical amount which is a physical amount relating to the machining of the workpiece and which can be detected at each of detection points which are set at predetermined intervals in a monitoring range for monitoring a state of the detectable physical amount, a storage device configured to store machining data which is actual detection data which is actually detected by the detection section, a group forming section configured to form one or multiple groups by dividing the actual detection data stored in the storage device in accordance with the number of the detection points which are set in advance in an interval from a monitoring start point to a monitoring end point of the monitoring range, and a setting section configured to set an upper limit value and a lower limit value of the monitoring range for each group of the groups formed by the group forming section based on the actual detection data belonging to each group.

A diagnostic apparatus (10) diagnoses the existence of an abnormality in a tool for processing of a processing target by each of multiple working machines. The diagnostic apparatus (10) includes an acquirer (110) and a diagnoser (160). The acquirer (110) acquires program identification information identifying a program executed in each of the working machines, tool information indicating a type of the tool applied to processing, and transition information indicating transition of load in the working machine from the start to the end of the processing executed by execution of the program, at execution of the processing in the working machine. The diagnoser (160) diagnoses whether an index value of the load obtained from the transition information is out of a predetermined range corresponding to a combination of the program identification information, the tool information, and machine information identifying the working machine that transmits the transition information.

The invention relates to a method for determining the degree of wear of at least one component of a machining device (10), wherein at least one actual condition (19) of the machining device (10) is established and the at least one actual condition (19) is compared to at least one comparative condition (18) of the machining device (10), and a conclusion is drawn as to the degree of wear of the at least one component as a function of a deviation determined between the at least one actual condition (19) and the at least one comparative condition (18), wherein, to establish the at least one actual condition (19) and/or the at least one comparative condition (18), sound emissions (16) of the machining device (10) are captured. The invention also relates to a device (13) for determining a degree of wear of at least one component of a machining device (10), a machining device (10) for machining workpieces (11), and a computer program for determining a degree of wear of at least one component of a machining device (10).