The controller communicable with a second controller include circuitry configured to: execute a processing to operate a first machine in collaboration with a second machine controlled by the second controller in a real space; modify the processing in response to determining that, instead of controlling the second machine, the second controller controls a virtual second machine that simulates operations of the second machine in a virtual space; and execute the modified processing to operate the first machine in the real space in collaboration with the virtual second machine that operates in the virtual space.

Methods and In an aspect a method of generating an instantaneous quote of any part without toolpathing, the method includes receiving, using a computing device, a geometric model of a part, constructing, using the computing device, at least a rotation-invariant feature as a function of the geometric model, predicting, using the computing device, a manufacturing time as a function of the at least a rotation-invariant feature and a manufacturing time machine learning model, selecting, using the computing device, a stock as a function of the at least a rotation-invariant and a stock selection machine learning model feature, and estimating, using the computing device, a quote as a function of the manufacturing time and the stock.

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.

One variation of a method for deploying sensors within an agricultural facility includes: accessing scan data of a set of modules deployed within the agricultural facility; extracting characteristics of plants occupying the set of modules from the scan data; selecting a first subset of target modules from the set of modules, each target module in the set of target modules containing a group of plants exhibiting characteristics representative of plants occupying modules neighboring the target module; for each target module, scheduling a robotic manipulator within the agricultural facility to remove a particular plant from a particular plant slot in the target module and load the particular plant slot with a sensor pod from a population of sensor pods deployed in the agricultural facility; and monitoring environmental conditions at target modules in the first subset of target modules based on sensor data recorded by the first population of sensor pods.

The present teachings relate to a method comprising: receiving at a user container runtime environment, via a container registry, an image of an obfuscated containerized model of an asset; wherein the containerized model comprises an API, and wherein the containerized model has been generated in a supplier runtime environment located within a supplier network environment, interfacing, with a model execution logic, the API of the containerized model image, wherein the interface comprises a process data signal that is transmitted to the API of the model image, and a model result data signal that is transmitted from the API of the model image; wherein the process data signal comprises data related to the usage conditions of the asset, and the model result signal is indicative of the response of the asset to at least some of the usage conditions, wherein the user container runtime environment is located within a user network environment which is isolated from the supplier network environment. The present teachings also relate to a method for transmitting a model of an asset, a method for transmitting an augmented model, a computer software product and a computer network arrangement.

A server that is a program providing device includes: a provision processing unit that provides a program part constituting a control program being a program to be executed in a controller; an authentication unit that authenticates an operation simulation module being a program for simulatively performing operation in accordance with the program part on a basis of a result of verification on whether or not the operation simulation module can simulate operation of the controller to be performed by execution of the program part; and an operation checking unit that checks operation of the program part by using the authenticated operation simulation module.

Methods, systems, and non-transitory computer readable medium are described for sensor metrology data integration. A method includes receiving sets of sensor data and sets of metrology data. Each set of sensor data includes corresponding sensor values associated with producing corresponding product by manufacturing equipment and a corresponding sensor data identifier. Each set of metrology data includes corresponding metrology values associated with the corresponding product manufactured by the manufacturing equipment and a corresponding metrology data identifier. The method further includes determining common portions between each corresponding sensor data identifier and each corresponding metrology data identifier. The method further includes, for each of the sensor-metrology matches, generating a corresponding set of aggregated sensor-metrology data and storing the sets of aggregated sensor-metrology data to train a machine learning model. The trained machine learning model is capable of generating one or more outputs for performing a corrective action associated with the manufacturing equipment.

Method, apparatus and computer program product for detecting vulnerability in an industrial control system, predicting maintenance in an industrial control system, and defining authorization rules for peripheral devices based on peripheral device categorization are described herein.

In an aspect of the disclosure, a method, a computer-readable medium, and an apparatus are provided. The apparatus may maintain an first dataset configured to select pick points for objects. The apparatus may receive, from a user device, a user dataset including a user selected pick point associated with at least one object and a first image of the at least one first object. The apparatus may generate a second dataset based at least in part on the first dataset and the user dataset. The apparatus may receive a second image of a second object. The apparatus may select a pick point for the second object using the second dataset and the second image of the second object. The apparatus may send information associated with the pick point selected for the second object to a robotics device for picking up the second object.

Disclosed is a method for monitoring and/or controlling a chemical plant (12) with multiple assets via a distributed computing system (10) with more than two deployment layers (14, 16, 30, 32, 34), wherein the deployment layers (14, 16, 30, 32, 34) comprise at least two of a first processing layer (14), a second processing layer (16, 32, 34) and an external processing layer (30), the method comprising the steps of: providing (60) a containerized application (48, 50) including an asset or plant template specifying input data, output data and an asset or plant model, deploying (62) the containerized application (48, 50) to execute on at least one of the deployment layers (14, 16, 30, 32, 34), wherein the deployment layer (14, 16, 30, 32, 34) is assigned based on the input data, a load indicator, or a system layer tag, and executing the containerized application (46, 52, 54) on the assigned deployment layer(s) (14, 16, 30, 32, 34) to generate output data for controlling and/or monitoring the chemical plant (12), providing (66) the generated output data for controlling and/or monitoring the chemical plant (12).