An assembly for monitoring a semiconductor device under test comprising a mill configured to mill the device, a sensor configured to measure an electrical characteristic of the device, and a computer configured to determine the amount of strain in the device from the electrical characteristic when the mill is milling the device and detect an endpoint of milling at a circuit within the device. In use the endpoints of the milling process of the semiconductor device are detected measuring an electrical characteristic of the device with a sensor during milling determining the amount of strain in the device from the electrical characteristic and detecting an endpoint of the milling process within the device based on the amount of strain.

An industrial machine including an actuator, a gear reducer, a cutter drum, a cutter bit, a sensor, and a controller. The gear reducer is configured to receive a first rotational energy from the actuator and output a second rotational energy. The cutter drum is supported by a chassis. The cutter drum is driven by the second rotational energy. The cutter bit is coupled to the cutter drum. The sensor is configured to sense a characteristic of the industrial machine. The controller, having a processor and memory, is configured to receive the characteristic of the industrial machine, determine a cutting efficiency based on the characteristic of the industrial machine, and output the cutting efficiency.

A control system for controlling oil-injection of a machine tool includes a sensor, a signal-processing device and a control device. The sensor senses movement of a machine component of the machine tool and outputs a sense signal to the signal-processing device. The signal-processing device derives analysis signals from the sense signal and sends the analysis signals to the control device. The control device determines whether to output an oiling signal to the machine tool to trigger an oiling device to oil the machine component according to an accumulated moving distance and a variation value that are calculated based on the analysis signals.

A control system for controlling oil-injection of a machine tool includes a sensor, a signal-processing device and a control device. The sensor senses movement of a machine component of the machine tool and outputs a sense signal to the signal-processing device. The signal-processing device derives analysis signals from the sense signal and sends the analysis signals to the control device. The control device determines whether to output an oiling signal to the machine tool to trigger an oiling device to oil the machine component according to an accumulated moving distance and a variation value that are calculated based on the analysis signals.

A piezoelectric sensing module, a piezoelectric sensing module detecting method, and a piezoelectric sensing detection system thereof are disclosed. The piezoelectric sensing module is used for an operating tool. The piezoelectric sensing module includes a piezoelectric sensing film, and the piezoelectric sensing film includes at least a first to a sixth electrodes; wherein the first electrode is disposed between the third and the fourth electrodes, the second electrode is disposed between the fifth and the sixth electrodes; wherein the first and the second electrodes, the third and the fifth electrodes, and the fourth and the sixth electrodes are separated by a certain distance respectively, and a first angle between the first and the second electrodes, a second angle between the third and the fifth electrodes, and a third angle between the fourth and the sixth electrodes each have an included angle of 90 degrees.

The disclosure provides a milling system and method under different lubrication conditions. The system uses a tool to mill the workpiece, a force measuring system to measure the milling force, a tool change system to replace the tools, a tool storage to store the tools. It can store the tools, provide the lubricating oil to the milling surface, select different tools according to different processing conditions, select the best angle differences of the unequal spiral angle tools according to different conditions comprising dry cutting, casting-type lubrication, minimal quantities of lubrication or minimal quantities of nanofluid lubrication, and/or choose the optimal tool according to different cutting parameters in order to obtain the minimum milling force.

The disclosure provides a method and system for milling injected cutting fluid under different working conditions. By analyzing influence of airflow fields in a milling area under different working conditions on injection of cutting fluid, an influence rule of a helical angle and a rotation speed of a cutter on the flow field is quantitatively analyzed, an optimal target distance of a nozzle, an angle between the nozzle and a milling cutter feeding direction and an angle between the nozzle and the surface of a workpiece are comprehensively determined, the nozzle is set according to a determined setting manner, and lubricating oil is sprayed to the milling area by utilizing the nozzle.

Provided is a machine tool including: a main shaft; feed-axis motors that relatively move a table and the main shaft in directions intersecting the longitudinal axis of the main shaft; feed-load measurement units that measure the magnitudes of loads applied to the feed-axis motors; and an anomaly detection unit that detects abnormal loads on the feed-axis motors when the magnitudes of the loads measured by the feed-load measurement units are greater than a predetermined threshold, wherein the predetermined threshold is changed according to the length of a tool that is held by the main shaft.

The present invention is directed to an automatic impact inducing device for inducing an impact on an object wherein, in particular on a machine tool.

An automated container cutting system includes a cutting tool configured to cut a container and a force feedback sensor operatively connected to the cutting tool. The force feedback sensor is configured to measure resistive force exerted on the cutting tool. The automated container cutting system includes a processor communicatively coupled to the force feedback sensor. The processor is configured to receive resistive force data from the force feedback sensor and determine whether the cutting tool has penetrated through the wall of the container using the received resistive force data.