A messaging system for exchanging messages between nodes in a network via a broker that uses a publish-subscribe message protocol, which nodes have object identifications (IDs). Messages between the nodes are routed using the object IDs of the nodes. Secure communication is provided using authentication according to digital certificates being used as first and second tiers by a commissioning broker and a data broker, respectively, in which the second tier certificate used by the data broker has a shorter lived expiration time.

An example method includes obtaining a geometric compensation profile characterising a relationship between a location of an object within a first fabrication volume having a first depth of build material and a geometrical compensation to be applied to a model of said object. The method further includes determining that a first object is to be generated in a first build operation having a second fabrication volume which has a second depth. The method may further include determining a geometrical compensation to be applied to a model of the first object by: determining a first offset of the first object from the top of the second fabrication volume; identifying the geometrical compensation value associated with a location having the first offset from the top of the first fabrication volume; and determining the compensation to be applied to the model of the first object based on the identified geometrical compensation value.

A schedule creation method is a method for creating a time schedule by executing a learning step multiple times. The learning step includes sequentially placing patterns each indicating a procedure in a processing sequence in a timetable for defining a time schedule for respective elements of a substrate processing apparatus. The sequentially placing patterns in a timetable includes: acquiring one or more placeable patterns that are allowed to be placed in the timetable from among the patterns based on a prescribed constraint condition; predicting and selecting through machine learning a pattern that makes an evaluation value maximum from among the one or more placeable patterns; and updating the timetable by placing the selected pattern in the timetable.

Provided herein are techniques related to an industrial system that may have a plurality of industrial automation devices, a database that has a plurality of location datasets that correspond to the plurality of industrial automation devices, and a monitoring system that may communicate with the industrial automation devices via a network and the database. The monitoring system may send a first request to the industrial automation devices in the industrial system to identify an industrial automation device having an active maintenance status. The active maintenance status may be indicative of a maintenance request for the industrial automation device. The monitoring system may send a second request to the database for a location dataset associated with the industrial automation device, generate a visualization that includes the active maintenance status and the location dataset associated with the industrial automation device, and display the visualization via an electronic display.

Systems and methods for flexible conveyance in an assembly-line or manufacturing process are disclosed. A fleet of self-driving vehicles and a fleet-management system can be used to convey workpieces through a sequence of workstations at which operations are performed in order to produce a finished assembly. An assembly can be transported to a first workstation using a self-driving vehicle, where an operation is performed on the assembly. Subsequently, the assembly can be transported to a second workstation using the self-driving vehicle. The operation can be performed on the assembly while it is being conveyed by the self-driving vehicle.

A method of detecting and classifying anomalies during semiconductor processing includes executing a wafer recipe a semiconductor processing system to process a semiconductor wafer; monitoring sensor outputs from a sensors that monitor conditions associated with the semiconductor processing system; providing the sensor outputs to models trained to identify when the conditions associated with the semiconductor processing system indicate a fault in the semiconductor wafer; receiving an indication of a fault from at least one of the models; and generating a fault output in response to receiving the indication of the fault.

Disclosed are threading device and threading method, including a turning step for threading a rotating workpiece with a predetermined cutting depth, by relatively moving a tool in the axial direction of the workpiece and then rounding-up the workpiece obliquely by relatively moving the tool in the axial direction and radially outward. The workpiece is subjected to the threading process by repeatedly carrying out the turning step while sequentially shifting the axial position for starting the rounding-up of the workpiece relative to an axial position where the rounding-up of the workpiece has been started in a previous turning step.

A method to simulate operations of a manufacture plant comprising a plurality of machines, the method including receiving a capacity function and an elapsed time function associated with a first machine of the plurality of machines, wherein the capacity function and elapsed time function is defined by one or more parameters characterizing the first machine, receiving a record of historical production data associated with the first machine, calculating, based on the capacity function and the record of historical production data, an augmented capacity function and an augmented elapsed time function that is defined by the one or more parameters and a quantity relating to parts waiting for processing (WIP), and simulating the operations of the plant based on the augmented capacity function and augmented elapsed time function.

The step for performing machine learning includes acquiring shape data; acquiring geometric information for each of a plurality of machining faces; acquiring a tool path pattern selected for the machining faces from among a plurality of tool path patterns; and performing machine learning by using the geometric data for known workpieces and the tool path patterns wherein the input is the geometric information for the machining faces and the output is the tool path pattern for the machining faces. The step for generating a new tool path includes: acquiring shape data for the workpiece; acquiring geometric information for each of the plurality of machining faces of the workpiece to be machined; and generating a tool path pattern for each of the plurality of machining faces on the workpiece on the basis of the results of the machine learning using the geometric information of the workpiece to be machined.

An object of the present subject matter is to appropriately acquire and analyze a camera image for monitoring and to constantly monitor a monitoring target with high accuracy. A programmable logic controller (PLC) includes: an image processing section for sequentially acquiring the image data of the camera image from the camera sensor and generating characteristic amount data indicating a characteristic amount of image data in a preset monitoring region; a time-series data acquisition section for sequentially collecting characteristic amount data from the image processing section and acquiring time-series data of a characteristic amount; and a monitoring section for monitoring time-series data of a current characteristic amount acquired by the time-series data acquisition section in accordance with a monitoring timing defined by the device of the device memory.