Embodiments of a downhole drilling assembly generally include a rotatable lower drilling assembly, a rotatable upper drilling assembly, and a drill bit, wherein the upper drilling assembly contains a mud motor adapted for clockwise rotation of its stator and counter-clockwise rotation of its rotor, whereby the lower drilling assembly is rotatable in the opposite direction of the upper drilling assembly or maintainable in a non-rotating state. The apparatus further includes sensors adapted to continuously measure physical properties and/or drilling parameters and a mechanism for continuously transmitting information relating thereto to the surface.

Embodiments of a method for operating a downhole drilling assembly generally include continuously measuring physical properties and/or drilling parameters proximate the drill bit, continuously transmitting information relating thereto to the surface, and controlling rotation of a lower drilling assembly in a non-rotating state or in the opposite direction of an upper drilling assembly by varying drill string rotation.

A machine tool controller includes: a voltage detection unit which detects a voltage value of an input power supply; a time measurement unit which measures an occurrence time and a duration time when a voltage drop state occurs with respect to the voltage value; an abnormality determination unit which determines whether a low voltage abnormality or a power failure occurs with respect to the input power supply based on the voltage value and the duration time of the voltage drop state; a machining management unit which acquires a machining condition command and machining information of the machine tool; and a storage unit which stores the voltage value detected by the voltage detection unit, the occurrence time of the voltage drop state measured by the time measurement unit, and the machining information when the abnormality determination unit determines that the low voltage abnormality occurs with respect to the input power supply.

A machine tool controller includes: a voltage detection unit which detects a voltage value of an input power supply; a time measurement unit which measures an occurrence time and a duration time when a voltage drop state occurs with respect to the voltage value; an abnormality determination unit which determines whether a low voltage abnormality or a power failure occurs with respect to the input power supply based on the voltage value and the duration time of the voltage drop state; a machining management unit which acquires a machining condition command and machining information of the machine tool; and a storage unit which stores the voltage value detected by the voltage detection unit, the occurrence time of the voltage drop state measured by the time measurement unit, and the machining information when the abnormality determination unit determines that the low voltage abnormality occurs with respect to the input power supply.

A system of isolation management comprises a computer for generating an isolation plan; a lockbox configured to receive the isolation plan from the computer; a mobile device associated with an individual, and one or more locks for isolation locking of an asset by each individual according to the isolation plan. The mobile device is allocated to the lockbox according to the isolation plan. The lockbox is configured to recognise the mobile device when proximal to the lockbox. The one or more isolation locks are removably housed in the lockbox. The one or more isolation locks are each able to be recognised by the mobile device and the mobile device is configured to record an association of one or more of the isolation locks to the mobile device according to the isolation plan. There is also an isolation point for isolating the asset with the one or more isolation locks according to the isolation plan. The isolation point is able to be recognised by the mobile device.

A face detecting and tracking method includes: acquiring an image and performing a face detection to determine one or more face boxes of each acquired image; performing a detection error removing process to the image of current frame, and saving one of the one or more face boxes of the processed image of current frame as a first face box; and determining a tracking box of the image of current frame based an the first face box and a tracked face box, and tracking the face in the tracking box of the image of current frame.

A face detecting and tracking method includes: acquiring an image and performing a face detection to determine one or more face boxes of each acquired image; performing a detection error removing process to the image of current frame, and saving one of the one or more face boxes of the processed image of current frame as a first face box; and determining a tracking box of the image of current frame based an the first face box and a tracked face box, and tracking the face in the tracking box of the image of current frame.

The present disclosure is intended to provide a technique which enables a direct visual comparison between a computationally-machined surface profile determined based on motor position information and a machined surface profile obtained by actual measurement of a machined surface. A display unit includes: a motor position information acquirer that acquires motor position information including at least one of a command position or a real position of a motor; a machine information acquirer that acquires machine information including a drive shaft configuration, a tool geometry, and a shape of an unmachined workpiece; a machined surface profile simulator that performs a simulation of machining a workpiece based on a machining program, and determines a computationally-machined surface profile of the workpiece simulated to be machined, based on the motor position information and the machine information; a machined surface profile measurer that measures a machined surface profile of a machined workpiece that has actually been machined based on the machining program; and a machined surface profile display that displays the computationally-machined surface profile determined by the machined surface profile simulator, in parallel with the machined surface profile measured by the machined surface profile measurer.

Method for controlling the operation of at least one machine (1), which is in particular configured to carry out pick-and-place or singulation tasks on objects (2), wherein the machine (1) comprises at least one functional device that comprises at least one functional element for carrying out at least one task, wherein the operation of the machine (1) is controlled on the basis of control information in order to carry out the at least one task, wherein the control information is generated on the basis of a plurality of task parameter types (APT) that relate to the operation of the machine (1) in order to carry out the task, wherein the task parameter types (APT) are stored on at least one data storage device (10) in a linked manner on the basis of predefined links specific to the task parameter types.

Method for controlling the operation of at least one machine (1), which is in particular configured to carry out pick-and-place or singulation tasks on objects (2), wherein the machine (1) comprises at least one functional device that comprises at least one functional element for carrying out at least one task, wherein the operation of the machine (1) is controlled on the basis of control information in order to carry out the at least one task, wherein the control information is generated on the basis of a plurality of task parameter types (APT) that relate to the operation of the machine (1) in order to carry out the task, wherein the task parameter types (APT) are stored on at least one data storage device (10) in a linked manner on the basis of predefined links specific to the task parameter types.

Method for monitoring and/or predicting machining processes and/or machining outcomes in mechanical workpiece machining carried out by a workpiece processing machine operable by specifiable operating parameters and having at least one machining tool. The monitoring and/or predicting occurs via a computer program product evaluation algorithm executed on a computer on the basis of training data sets. The training data sets include, as training data, adjustment data relating to adjustment of operating parameters of the workpiece processing machine for carrying out a machining process to be monitored and/or predicted. The training data sets further include outcome data of workpieces finished in a machining process to be monitored and/or predicted, and state data of the processing machine, determined by sensor, during a machining process to be monitored and/or predicted. In use, capture of outcome data by prediction made on the basis of machine-learned knowledge is avoided or reduced.