An operational control method is provided for a machine tool that includes a plurality of tool holders with a cutting-tool. The machine tool relatively moves the tool holders with respect to a workpiece to process the workpiece. The operational control method includes determining whether an abnormality has occurred in the cutting-tool during a processing or not, determining whether a simultaneous processing in which at least two or more of the tool holders perform the processings to an identical workpiece is being performed or not and whether the cutting-tool having the detected abnormality is the cutting-tool that is performing the simultaneous processing or not when the abnormality is detected, and causing the tool holder with the cutting-tool having the detected abnormality to take an abnormality avoidance operation and another of the tool holders to take a response operation based on a determination result at the determining of the simultaneous processing.

Methods, systems, and apparatuses relating to augmented-reality interfaces. Features of the present invention rely on robust touch detection methods, touch detection methods, calibration methods, and integrated projector and sensor apparatuses.

A wire disconnection prediction device includes: a data acquisition part configured to acquire data relating to machining of a workpiece during machining of the workpiece by a wire electric discharge machine; a preprocessing part configured to create, based on the data acquired by the data acquisition part, machining condition data, machining member data and machining state data, as state data indicating a state of the machining; and a machine learning device configured to execute, based on the state data created by the preprocessing part, processing relating to machine learning using a learning model indicating correlation between a machining state in the wire electric discharge machine and presence/absence of a possibility of disconnection occurrence of a wire electrode in the wire electric discharge machine and a disconnection cause by a plurality of class sets.

Methods and system for implementing Condition Based Maintenance (CBM) of downhole systems and equipment, including drilling tools, wireline tools and production tools is presented in this disclosure. The presented CBM-based approach combines the use of a tool life distribution with a life-stress acceleration model and a time-varying stress model to model failure times of a tool. One or more failure parameters related to operation of the tool during the operational run can be calculated based on a life measure of the tool determined for each step in the series of steps of the operational run, a time duration of each step, and a life duration of the tool at reference levels of stress variables. Maintenance of the tool can be performed based on the calculated failure parameters.

Methods and system for implementing Condition Based Maintenance (CBM) of downhole systems and equipment, including drilling tools, wireline tools and production tools is presented in this disclosure. The presented CBM-based approach combines the use of a tool life distribution with a life-stress acceleration model and a cumulative damage model to account for varying stress levels during a tool operation. The CBM methodology presented herein provide for a more effective maintenance system based on direct utilization of field data so that an appropriate maintenance can be performed at an appropriate time, thereby optimizing a frequency of performing maintenance.

A tool monitoring device and method for using a tool monitoring device, the tool monitoring device including a housing configured to couple with an exterior surface of a tool, one or more sensors positioned within the housing and configured to measure one or more properties of the tool over a period of time, a communication interface configured to transmit data from the tool monitoring device to one or more external devices, the transmitted data being generated based at least in part on the measured one or more properties of the tool over the period of time, and a power source configured to provide power to the one or more sensors and the communication interface.

A tool monitoring method and a tool monitoring system are provided. The tool monitoring method includes extracting a first data and a second data of a tool of a machine tool, simulating and analyzing the first data to generate a comparison value, calculating the second data to obtain an actual value, and integrating and comparing the comparison value with the actual value to produce a comparison result for monitoring the operating condition of the tool.

An attachment tool includes an image capturing unit configured to capture an image of a random pattern provided on a comparison region of a part; and an identification result-outputting unit configured to output a part identification result obtained by comparing an image characteristic of the captured image of the random pattern with a previously stored image characteristic of a random pattern of a part.

A portable lifting arm includes a base, a plurality of casters fixed to a bottom side of the base, an arm mounting structure extending upward from a top side of the base, and an arm. The arm includes a first arm segment having a first end and a second end, the first end of the first arm segment being attached to the arm mounting structure, a second arm segment having a first end and second end, the first end of the second arm segment rotationally connected to the second end of the first arm segment, and a power tool rotationally connected to the second end of the second arm segment. A controller in electrical communication the power tool selects between predetermined settings on the power tool based on a position of the first arm segment and the second arm segment relative to the arm mounting structure.

An abnormality determination apparatus of the present invention acquires state data from work equipment provided with an attaching part to which a plural kinds of work parts are attached in a replaceable manner, identifies the kind of a work part attached to the attaching part, sets, corresponding to the identified kind of the work part, abnormality determination data for determining an abnormality of the work equipment, acquires, from among state data acquired from the work equipment, state data of a time when the identified kind of the work part was being attached, and compares the acquired state data with the set abnormality determination data to determine an abnormality of the work equipment.