A base software application and an operation software application are installed in a machine control computer. The base software application includes a first communication unit being a program portion, a second communication unit being a program portion, and an information conversion unit being a program portion. The information conversion unit enables a CPU of the computer to convert first machine information specific to a machine into second machine information specific to the operation software application, based on a data model or the like corresponding to a category of the machine or the like.

A method includes receiving a matrix including start times associated with substrate operations in a substrate processing system. The method further includes generating, by a first graphics processing unit (GPU) of one or more GPUs, a plurality of matrices based on the matrix. The method further includes concurrently processing, by a plurality of cores of the one or more GPUs, the plurality of matrices to generate parallel outputs. A schedule for processing substrates in the substrate processing system is to be generated based on the parallel outputs.

A generalization and encapsulation method based on a digital twin (DT) model of a workshop includes: classifying a device in a production line according to a basic operation and a functional characteristic of a process of the device; abstracting a commonality in terms of process action mode, process algorithm and action trigger mechanism; encapsulating according to a sequence characteristic of a process; comparing processes, and generalizing and encapsulating; encapsulating according to a time sequence, a space sequence and a logic characteristic of a specific process; storing a generalized and encapsulated process in a database; and calling the generalized and encapsulated process from the database to a device or a process. The generalization and encapsulation system includes an abstract process encapsulation module, a continuous process encapsulation module, a process action encapsulation module, a process algorithm encapsulation module, a database and a fast calling module.

A sensing system provided with a target detecting unit which applies predetermined processing to data obtained by a detecting device and thereby detects a target object, the sensing system including an augmented-reality-image creating unit which creates an image corresponding to a candidate in a plurality of candidates that appear in the processed data to which the predetermined processing has been applied, a predetermined parameter of the candidate being equal to or greater than a detection threshold, and creates a candidate image corresponding to a candidate in the plurality of candidates, the predetermined parameter of the candidate for the candidate image is less than the detection threshold and equal to or greater than a detection candidate threshold, and a display device that displays the image and the candidate image.

One or more aspects of the present invention relate to a computer-implemented method for part analytics, in particular for analyzing the quality, the machining process and preferably the engineering process, of a workpiece machined by at least one CNC machine. According to these aspects, the method may include providing a digital machine model of the CNC machine with realtime and non-realtime process data of the at least one CNC machine, the realtime and non-realtime process data being recorded during the machining process of the workpiece under consideration; and subsequently simulating the machining process under consideration by means of the digital machine model based at least partially on the recorded realtime and non-realtime process data.

The present invention relates to the field of intelligent machining, in particular to a parallel control method based on multi-period differential sampling and digital twinning technologies, the method comprising the following steps of: a. detecting machining conditions of dotting machine equipment by using a multi-period differential sampling technology; b. establishing a digital twinning control model; and c. controlling a simulation model of the dotting machine equipment according to a detection judgment result so as to perform parallel control on the dotting machine equipment. According to the parallel control method based on multi-period differential sampling and digital twinning modelling provided by the present invention, for the digital twinning model of the dotting machine equipment, the parallel control method establishes a simulation model and a detection model of the dotting machine equipment by using a virtual-real synchronization technology; simulation dotting machine equipment operates in synchronization with the physical dotting machine equipment.

The subject technology is related to methods and apparatus for discretization and manufacturability analysis of computer assisted design models. In one embodiment, the subject technology implements a computer-based method for the reception of an electronic file with a digital model representative of a physical object. The computer-based method determines geometric and physical attributes from a discretized version of the digital model, a cloud point version of the digital model, and symbolic functions generated through evolutionary algorithms. A set of predictive machine learning models is utilized to infer predictions related to the manufacture process of the physical object.

A method includes receiving a matrix including start times associated with substrate operations in a substrate processing system. The method further includes generating, by a first graphics processing unit (GPU) of one or more GPUs, a plurality of matrices based on the matrix. The method further includes concurrently processing, by a plurality of cores of the one or more GPUs, the plurality of matrices to generate parallel outputs. A schedule for processing substrates in the substrate processing system is to be generated based on the parallel outputs.

The present invention relates to the field of intelligent machining, in particular to a parallel control method based on multi-period differential sampling and digital twinning technologies, the method comprising the following steps of: a. detecting machining conditions of dotting machine equipment by using a multi-period differential sampling technology; b. establishing a digital twinning control model; and c. controlling a simulation model of the dotting machine equipment according to a detection judgment result so as to perform parallel control on the dotting machine equipment. According to the parallel control method based on multi-period differential sampling and digital twinning modelling provided by the present invention, for the digital twinning model of the dotting machine equipment, the parallel control method establishes a simulation model and a detection model of the dotting machine equipment by using a virtual-real synchronization technology; simulation dotting machine equipment operates in synchronization with the physical dotting machine equipment.

A computer apparatus runs a hydraulic model using real-time or near-real-time data from an Automated or Advanced Metering Infrastructure (AMI), to improve model accuracy, particularly by obtaining more accurate, higher-resolution water demand values for service nodes in the model. Improving the accuracy of water demand calculation for the service nodes in the model stems from an improved technique that more accurately determines which consumption points in the water distribution system should be associated with each service node and from the use of real-time or near-real-time consumption data. The computer apparatus uses the water demand values to improve the accuracy and resolution of its water flow and pressure estimates. In turn, the improved flow and pressure estimation provides for more accurate control, e.g., pumping or valve control, flushing control or scheduling, leak detection, step testing, etc.