Abstract: An information processing device includes: a machine learning model selection part configured to select a machine learning model appropriate for a data set used for learning of the machine learning model; a calculation part configured to perform an optimization calculation by using the selected machine learning model to calculate process conditions that can achieve a target process result, predicted values of a process result corresponding to each of the process conditions, and reliability of the predicted values; a process condition selection part configured to select, among the process conditions that can achieve the target process result, one or more process conditions according to the predicted values of the process result and the reliability of the predicted values; and a display controller configured to display the selected process conditions, the predicted values of the process result corresponding to each of the selected process conditions, and the reliability of the predicted values.

Abstract: There is provided a control system for an apparatus for taking out a molded product, the apparatus performing appropriate operation when a collision occurs while a servo system control section is manually operated. When a collision detection section outputs an operation stop command, a deviation clearing section performs clearing operation to bring deviations in a servo system control section to zero with the servo system control section kept on. Positioning is completed as the deviations are brought to zero, which enables operation to be performed again. When a retracting operation is performed after the operation is stopped, servomotors are operated according to an operation command, which allows smooth retraction from the collision state.

Abstract: A method for tracking a component in a production line having a plurality of processing systems includes processing and/or testing, by each of the processing systems, the component, providing a processing signal characterizing the processing and/or testing for a higher-level electronic computing unit, and tracking, by the computing unit based on the received processing signals, the component through the production line. A query signal characterizing a component property of one of the processing systems of the production line is received by the computing unit. The component is ascertained by the computing unit and at least one component information signal characterizing the component property of the ascertained component is provided.

Abstract: The present disclosure discloses an industrial Internet of things with a sensor network platform in a front sub platform type, comprising: a user platform, a service platform, a management platform, a sensor network platform, and an object platform which are interacted sequentially. The sensor network platform adopts front sub platform layout, which can process data for different target objects, and then summarize data, so as to reduce the data processing capacity of entire sensor network platform. The management platform is arranged independently to form multiple independent data processing channels of the same or different. The gateway on each communication network shares part of the calculation for the management platform, effectively reducing the calculation pressure of the management platform, and ensuring that the data is transmitted according to a specific path or processed by a specific server, so as to ensure the safety and independence of the data.

Abstract: A system and method for determining a local CVR factor using grid edge devices (GEDs) comprises: receiving, from each of the GEDs, respective voltage change values and power change values; identifying, using the processor, voltage events within at least one control zone, each of the GEDs being associated with a zone of the at least one control zone, the voltage events being identified based on the GEDs in the groups meeting one or more event parameters; identifying a plurality of CVR values for each GED, each CVR value being based on one of the voltage change values and one of the power change values associated with each identified voltage event; generating, using the processor and based on the plurality of CVR values, a local CVR factor for each GED; and, controlling one or more devices based on the local CVR factor.

Abstract: In a method and device for assessing the quality of a processing operation, a workpiece with specific processing parameters is processed along a processing trajectory. The (X), wherein the processing result is measured by at least one sensor and at least one sensor signal is recorded and at least one quality parameter is determined based on at least one sensor signal and the at least one quality parameter is compared with quality parameter threshold values to assess the quality of the processing result. During the assessment of the processing operation quality, changes made to the processing parameters from target values during the processing are automatically taken into consideration, in that, instead of the quality parameter threshold values, quality parameter threshold values adapted to the changes in the processing parameters are determined, and the at least one quality parameter for assessing the quality of the processing result is compared with the adapted quality parameter threshold values.

Abstract: A continuous flow manufacturing system includes a tool, configured to hold a part. The system also includes a machine-readable identifier, associated with the tool and encoded with a tool-identification. The system further includes a plurality of workstations. Each one of the plurality of workstations includes a production machine, configured to perform a manufacturing operation on a part, and a reader, configured to read the machine-readable identifier. The system also includes a computing device, configured to retrieve process-data, associated with the tool-identification and a corresponding one of the plurality of workstations, and configured to update the process-data, subsequent to performing the manufacturing operation associated with the corresponding one of the plurality of workstations.

Abstract: A controller and related system and method for controlling a choke for choking fluid flow are configured to take into account non-linear behaviors of the choke, to allow more accurate and effective control of the choke. To obtain a desired pressure drop across a choke valve, the controller is configured to monitor the position of a choke actuator coupled to the choke valve and the pressure at the inlet of the choke valve. The controller calculates an adaptive proportional gain coefficient, and optionally adaptive integral and derivative coefficients, based on the choke actuator position, to help mitigate the effects of non-linear behaviors of the choke and, where necessary, based on the inlet pressure, the controller calculates an augmentation correction to address any instability in the choke. The controller then commands the choke actuator accordingly to adjust the flow area through the choke valve.

Abstract: Residual limit determination for a cleaning agent corresponding to a validation of an equipment cleaning process is presented herein. A system determines a cleaning agent for cleaning a group of equipment to be used to manufacture a product; and determines a sum of surface areas of respective surfaces of respective groups of parts of the group of the equipment that have been determined to be contacted by the product and the cleaning agent. Based on the sum of surface areas of the respective surfaces that have been determined to be contacted by the product and the cleaning agent, the system determines a cleaning agent residue limit representing a threshold maximum allowable residue of the cleaning agent to be present after the cleaning process has been performed on the group of equipment, and facilitates a cleaning validation of the cleaning process according to the cleaning agent residue limit.

Abstract: A plant monitoring device (20) is provided with: a state quantity acquiring unit (211) which acquires state quantities for each of a plurality of characteristic items relating to a plant; an abnormality degree calculating unit (212) which calculates a degree of abnormality representing a degree of approach toward an abnormal side relative to a limit value that is predetermined for each characteristic item, for the state quantities acquired at a plant monitoring timing; a distance calculating unit (213) which uses a statistical technique to calculate distances representing the degrees of separation, from the normal operating state of the plant, of the state quantity and the degree of abnormality acquired at the monitoring timing; and a determining unit (214) which determines the operating state of the plant on the basis of the calculated distances.

Abstract: One or more systems, devices, and techniques for heating a structure using boiler water stored by a boiler are described herein. For example, a method includes obtaining gas consumption data for a heat source that is heating a structure and obtaining zone and ambient temperature data while the structure is being heated. Additionally, the method includes estimating unknown parameters of elements of a dynamic heat loss model as part of a model predictive control (MPC) model for the structure using inverse modeling as a function of the obtained gas consumption data and zone and ambient data.

Abstract: A method for forming a stamped component from a blank material with an industrial stamping machine during a stamping process includes measuring a plurality of parameters of the stamping process. The parameters are provided as variables of the stamping process. The method further includes analyzing, by a stamping process model, the plurality of parameters to adjust the stamping process for the blank material, defining, by the stamping process model, a control parameter of the industrial stamping machine for the blank material, and stamping the blank material with the industrial stamping machine based on the defined control parameter to form the stamped component.

Abstract: One or more systems, computer-implemented methods and/or computer program products to facilitate a process to monitor and/or facilitate a modification to a manufacturing process. A system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise an initialization component that identifies values of inflow data of one or more inflows of a set of inflows to a manufacturing process as control variables, and a computation optimization component that optimizes one or more intermediate flows, outflows or flow qualities of the manufacturing process using, for mode-specific regression models, decision variables that are based on a set of joint-levels of the control variables. An operation mode determination component can determine operation modes of the manufacturing process that are together defined by a set of joint-levels of the control variables.

Abstract: Heating operation control includes obtaining sensor data indicating measured temperatures within a heating vessel during a heating operation; determining sets of thermal stack parameters. Each set of candidate thermal stack parameters is descriptive of a respective configuration of a thermal stack modeled by a first machine learning model to generate one or more estimated tool temperature values. The thermal stack includes the tool and a part coupled to the tool. Heating operation control also includes determining a temperature profile for the heating operation. The temperature profile is determined, via a second machine learning model, based on the plurality of sets of thermal stack parameters and one or more process specifications of the thermal stack.

Abstract: A control device is configured to cause an output of a target device to be servo-controlled to follow a predetermined command in a predetermined working coordinate system.

Abstract: A water supply control system is disclosed that comprises a computer-implemented control system coupled to a plurality of gates, one or more pumps, and a plurality of sensors. The computer-implemented control system is configured to receive a request to transfer excess water from a non-water supply lake to a water supply lake and determine, based at least in part on data from the plurality of sensors and geographic locations of the non-water supply lake and the water supply lake, whether transferring water as requested will cause or worsen a flood event. In response to a determination that transferring water as requested will not cause or worsen a flood event, the computer-implemented control system is further configured to issue a command to cause a gate associated with a dam at the non-water supply lake to open such that water is transferred from the non-water supply lake to the water supply lake.

Abstract: A robot and work equipment are disposed near a work table including a work table-side controller and a process planning and designing controller capable of being operated by a user. The work table-side controller executes a work process in which the robot and the work equipment operate in conjunction, by receiving signals carrying identification and state monitoring information from a robot-side controller and the work equipment and then sending these signals to the process planning and designing controller, and by sending operation command signals to the robot-side controller and the work equipment in accordance with the aforementioned work process and then receiving operation status signals from the robot-side controller and the work equipment. Based on the signals carrying the identification and state monitoring information on the robot and the work equipment, the process planning and designing controller plans and designs the aforementioned work process.

Abstract: A method of controlling a thermal system of an industrial process includes monitoring intermediate data, associating the intermediate data with correlation data, wherein the correlation data includes an internal process control input, an external heater control input, the output control, or a combination thereof. The method further includes generating a model that defines a relationship between the intermediate data and the correlation data, identifying a state of the heater system based on the model, and selectively performing a corrective action based on the identified state of the heater system.

Abstract: A method, apparatus, and system for manufacturing a composite part. A set of reference locations is identified for a set of fiducial markers on a composite ply from a ply shape model for the composite part. The set of fiducial markers is created at the set of reference locations on the composite ply. The composite ply is cut to have a shape defined by the ply shape model.

Abstract: A machine learning device includes a data extraction unit that extracts first and second parameters from a plurality of machining programs. The machining programs numerically control a machine tool. The first parameter is a parameter to be adjusted, and the second parameter is a parameter used to adjust the first parameter. The machine learning device also includes a machine learning unit that learns a value of the first parameter according to a data set that includes the first and second parameters.