A method for controlling a virtual assistant for an industrial plant includes receiving by an input interface an information request, wherein the information request comprises at least one request for receiving information about at least part of the industrial plant; determining by a control unit a model specification using the received information request; determining by a model manager a machine learning model using the model specification; and providing by the control unit a response to the information request using the determined machine learning model.

In one embodiment, a system includes a wafer handling system, processing components, a controller, a virtual assistant, a natural language processing (NLP) engine, and a data-analytics engine. The wafer handling system is configured to hold one or more wafers for processing. The processing components is configured to physically treat the one or more wafers. The controller is configured to operate the processing components. The virtual assistant, in communication with the NLP engine, is configured to receive a user query from a user, understand an intent or context of the user query, and provide a context-specific response to the user query. The data-analytics engine is configured to generate and provide analytical data relating to the user query based on data collected from a plurality of data sources via one or more communication protocols.

A cloud-based industrial controller that controls devices, processes, and other assets of an industrial automation system via control algorithms that execute on a cloud platform is presented. A cloud-based collection component collects information from the industrial automation system via cloud gateways associated with the industrial automation system or extrinsic data sources. The cloud-based industrial controller can monitor and analyze the information, generate control instructions based on the analysis results, and communicate the control instructions to the devices, processes, and/or other assets of the industrial automation system to control operation of the industrial automation system. The cloud-based industrial controller also can interface with a industrial plant-based industrial controller, wherein the cloud-based industrial controller can determine supplemental control instructions to the industrial plant-based industrial controller, based on the information, including extrinsic information, to assist in controlling the industrial automation system and control decision-making.

Systems for reducing reduce downtime include industrial machines, sensor(s) associated therewith, edge agent(s), central controller(s), and display(s). The sensor(s) detect operational parameters (e.g., error condition) of the industrial machines associated therewith. The edge agent(s) receive information (e.g., logging messages) from the industrial machines and/or information from the sensors. The central controller(s). The central controllers receive and transform the information into standardized logging messages that are formatted identically, analyze the standardized logging messages to determine occurrence(s) of a current or anticipated error condition for any of the industrial machines, and transmit an alert and/or notification to the display(s) so users can take corrective action to ensure proper operation of the industrial machines. Such a system can be used in performing a corresponding method for reducing downtime associated with current or anticipated error conditions of such industrial machines.

A work support apparatus holds a value indicating information on at least one of an apparatus used for a work and a worker, a work change recognition determination algorithm, and a work support content corresponding to a determination result, applies a value indicating information on at least one of the apparatus and the worker to the work change recognition determination algorithm, determines whether or not the worker recognizes a work change indicating at least one of a change in a work process and a transition between a normal state and an abnormal state of a work, and outputs, to the output device, a work support content corresponding to the determination result.

The invention relates to a method which is used to operate an injection molding machine for processing plastics, which has a mold closing unit (F) for opening and closing an injection mold (M) having at least one mold cavity (12) in order to produce an injection molded part (13), an injection molding unit (S) for plasticizing and injecting new plasticizable material into the mold cavity (12), and a control system (11) for operating the injection molding machine (10). Stored in the control system is expert knowledge (E) about the operation of the injection molding machine and the peripheral devices (P) of the latter which may possibly be present and about the production of injection molded parts (13) using injection molding technology, in order to produce an injection molded part (13) using interactive contact as needed by an operator by using injection molding parameters. The fact that, in further steps, information about the component or the mold cavity (12) is provided to the control system (10) means that the plant and process parameters required for the production of the injection molded part (13) can be calculated by the control system (10) before the first injection molded part is produced, such that an alternative procedure for the operator-friendly setting of a machine for processing plastics is made available.

The present invention relates to a method and a system for controlling a process of a process plant. Hie system is configured to control a process in the process plant by recommending control operations and perform the control operations. The system obtains the control operations and detects availability of control room operators using historical data related to actions performed by the control room operators, sensory parameters of the control room operators and a status associated with the process. The system provides queries related to the control operations, the plant parameters, status of the process to the control room operators upon detecting the availability. Hie queries are validated by the control room operators. The system thereafter autonomously controls tire control room based on the validated data.

A work instruction system includes: a production progress management device including a communication unit configured to communicate with a work instruction device, a product signal storage unit that stores a product signal including position information of a product, a product in-progress process estimation unit configured to estimate an in-progress process of the product using the position information, and a production progress estimation and update unit configured to estimate production progress of the product in accordance with a change in the position information and update production progress information; and the work instruction device including a communication unit configured to communicate with the production progress management device, a production progress storage unit that stores the production progress information, a data collection unit configured to obtain progress management information updated from the production progress management device, a recommended work generation unit configured to generate recommended work information, and an output unit.

An intrinsically-safe handheld field maintenance tool includes a controller, a process communication module, and a display. The process communication module is configured to communicate with a field device using a process communication protocol. The display is coupled to the controller. A user interface module is also coupled to the controller and is configured to receive user input. The controller is configured to detect a user input help request and provide a video output on the display in response to the user input help request.

A semi-automatic welding work cell, including a welding job sequencer that automatically selects a welding schedule for use by an operator in the semi-automatic welding work cell. The automatic selection may be by way of elapsed time, a detection of welding operations, a detection of the amount of welding wire supplied for the welding operation, or a detection of the amount of energy supplied for the welding operation.