Abstract: A system may automatically control a pipeline heating system to maintain a desired temperature and/or to provide flow assurance of process fluid along a pipeline. The system may identify the occurrence and location of the solidification of a given process fluid or the melting of the given process fluid by monitoring temperatures along the pipeline and identifying from the monitored temperatures the occurrence and location of a latent heat signature associated with the solidification or melting of the given process fluid. The system may calculate and display fill percentages of the solidified process fluid at locations along the pipeline. The system may determine the percentage of a given section of pipeline that is filled with solid and/or liquid process fluid on a meter-by-meter basis. The system may perform automated re-melt operations to resolve plugs of solidified process fluid that may occur in the pipeline.

Abstract: A production management device, such as a production management computer, determines a production sequence of plural types of substrates in order to produce the substrates consecutively on a product type-by-type basis by using a component mounter including component supply devices. The production management device includes a main control unit for determining a production sequence of substrates such that, where a time from start to completion of off-line setup of all the component supply devices to be used for a single product type of substrate is defined as an off-line setup time, a sum of the off-line setup times for two product types of substrates to be consecutively produced is balanced over an entire period of consecutive production.

Abstract: A method of commissioning or maintenance an alarm system is provided. The method including: receiving a fault report including one or more faults from an alarm system; categorizing the one or more faults; prioritizing the one or more faults into a list of highest priority; determining a first root cause of a first fault of the one or more faults in response to at least one of an alarm system configuration of the alarm system, a device mapping of the alarm system, and an event history of the alarm system; providing instructions, via a user interface, regarding how to resolve the first fault in response to the first root cause; and detecting whether the first fault is resolved.

Abstract: Examples relate to adjusting load power consumption based on a power option agreement. A computing system may receive power option data that is based on a power option agreement and specify minimum power thresholds associated with time intervals. The computing system may determine a performance strategy for a load (e.g., set of computing systems) based on a combination of the power option data and one or more monitored conditions. The performance strategy may specify a power consumption target for the load for each time interval such that each power consumption target is equal to or greater than the minimum power threshold associated with each time interval. The computing system may provide instructions the set of computing systems to perform one or more computational operations based on the performance strategy.

Abstract: Disclosed herein is a method and system for sharing power or energy across various power supply and control modules. More specifically, disclosed herein are systems and methods for distributing energy. As explained herein, the method discloses receiving, at a microgrid, data from a plurality of data sources. The data is then analyzed to forecast power needs associated with the microgrid. Using the data, the microgrid may determine whether and when to share power with the requesting module.

Abstract: A method, device for identifying causes of faults in automated systems and an automated system which forms the device for identifying causes of faults in automated systems, wherein within a digital twin of the automated system, at least one element of the digital twin is assumed to be faulty and then simulated using the digital twin until a fault time, and where at least one faulty element of the automated system is identified as the cause of a fault based on the at least one element assumed to be faulty.

Abstract: A numerical controller includes an activation unit that builds a memory map according to settings when the power is on; a change detection unit that detects an operation requiring reconstructing of the memory map; a task control unit that, when the operation is detected, performs a stopping process of a task being operated; and a memory map control unit that, after the task has stopped, acquires a backed up memory, reconstructs the memory map according to the setting, and compares the reconstructed memory map and the backed-up memory map, and resets information required for operating the task again such as a program counter.

Abstract: Some implementations of the disclosure are directed to tapping input/output (I/O) data from an industrial control system (ICS) or applying the tapped I/O data to a learned model to perform predictive or prescriptive maintenance. In one implementation, a method comprises: tapping I/O data from a controller of an ICS while the controller executes first control code to control one or more devices of the ICS; transmitting the tapped I/O data over a network to a second system; and executing, via the second system, second control code comprising an original or modified version of all or a subset of the first control code of the ICS, wherein the second control code executes in response to receiving the tapped I/O data. The output of executing the second control code may be provided to a model to predict a future event involving the ICS or to prescribe maintenance of the ICS.

Abstract: A simulation device has a simulation unit and a coordinate acquisition unit. The simulation unit simulates the operations of press devices and the operations of feeder devices that transport a workpiece between the press devices. The coordinate acquisition unit acquires a locus of a plurality of predetermined positions in the width direction of the feeder devices from simulation.

Abstract: The present invention discloses a networked control system (NCS) time-delay compensation method based on predictive control. The method comprises the following steps: (1) acquiring random time-delay data in an NCS, and preprocessing the data; (2) predicting the current time-delay by using a fuzzy neural network (FNN) optimized by a particle swarm optimization (PSO) algorithm; (3) compensating the predicted time-delay by using an implicit proportional-integral-based generalized predictive control (PIGPC) algorithm; (4) determining whether a preset work end time is up according to a clock in the NCS; if yes, ending the process; if no, returning to step (2). The method disclosed by the present invention can accurately predict and effectively compensate the NCS time-delay and has excellent development prospect.

Abstract: The present disclosure is directed to systems and methods for economically optimal control of an electrical system. A two-stage controller includes an optimizer and a high speed controller to effectuate a change to one or more components of the electrical system. The high speed controller receives a set of control parameters for an upcoming extended time period. The control parameters include a plurality of bounds for an adjusted net power of the electrical system. The high speed controller sets an energy storage system command control variable (ESS command) based on a state of adjusted net power of the electrical system and the set of control parameters.

Abstract: A computer implemented method of analyzing measurement results of a target system, such as an industrial process or communication network. The method includes receiving a data sample with a plurality of variables representing the measurement results, detecting that the data sample is an anomalous sample using an anomaly detection model, processing the data sample by applying an imputation model to selected subsets of variables of the data sample to obtain imputed samples, and applying the anomaly detection model to the imputed samples, determining anomalous variables of the data sample based on results from the processing of the data sample, and outputting the anomalous variables of the data sample for management operations in the target system.

Abstract: Methods and systems for training and implementing metrology recipes based on performance metrics employed to quantitatively characterize the measurement performance of a metrology system in a particular measurement application. Performance metrics are employed to regularize the optimization process employed during measurement model training, model-based regression, or both. For example, the known distributions associated with important measurement performance metrics such as measurement precision, wafer mean, etc., are specifically employed to regularize the optimization that drives measurement model training. In a further aspect, a trained measurement model is employed to estimate values of parameters of interest based on measurements of structures having unknown values of one or more parameters of interest. In a further aspect, trained measurement model performance is validated with test data using error budget analysis.

Abstract: A method of monitoring and controlling an industrial process includes capturing images of a non-sensible process condition of the industrial process with an image capture device, receiving the images of the non-sensible process condition with a computer system, and converting each image into a corresponding numeric value with a machine learning model stored in and operable by the computer system. The corresponding numeric value is then received and compared to a predetermined numeric value for the non-sensible process condition with a closed-loop controller, and an actuator operates with the closed-loop controller to adjust operation of the industrial process when the corresponding numeric value fails to match the predetermined numeric value or is outside of a defined threshold near the predetermined numeric value.

Abstract: An object is to read the information of a feature shape included in a machining program so as to calculate a control command suitable for machining processing on the feature shape. A numerical controller (300) includes: a feature detection unit (302) which detects the feature of a machined shape from a machining program that commands the movement of a tool or a workpiece; an inward-turning amount calculation unit (303) which calculates, based on a servo parameter of a servo controller (400) that drives the tool or the workpiece, the feature of the machined shape detected from the machining program and a machining requirement that specifies a machining condition, a relation formula that determines the inward-turning amount of a machining path with respect to a program path; and a feedrate determination unit (304) which determines a feedrate that is optimized with the relation formula.

Abstract: A method for automating system identification includes performing a system identification experiment, and performing a system identifying processing by fitting a model to data from the system identification experiment. The method also includes performing model reduction to generate a model numerically suitable for controller synthesis by removing inconsequential states that cause controller optimization methods to fail. The method further includes performing control synthesis using the generated model or reduced models, including disturbance spectrum estimates, to generate a candidate controller design to be used during system operation. The method also includes checking for controller robustness using the identified model to ensure stability of the system while maximizing closed-loop bandwidth and performance.

Abstract: A system for diagnosing an additive manufacturing device is provided. The system includes a first module configured to: obtain one or more parameters for a digital twin of a component of the additive manufacturing device based on raw data from the component of the additive manufacturing device; and generate physics features for the digital twin of the component of the additive manufacturing device based on the one or more parameters and one or more transfer functions, a second module configured to obtain one or more classifiers for classifying the component as a first condition or a second condition based on physics features; and a third module configured to: determine a health of the component based on the generated physics features of the first model and the one or more classifiers.

Abstract: This control device of a machine tool is provided with: a storage unit which stores in advance a nominal diameter and a nominal length of a blade part of a rotary tool; an image-capturing instruction unit which outputs an image-capturing instruction to an image-capturing device; a model creation unit which generates model data of the blade part of the tool on the basis of the nominal diameter and the nominal length stored in the storage unit, generates model data of a tool shank and holder on the basis of an image stored in the image-capturing device, and creates model data of the rotary tool on the basis of the generated model data of the blade part and the generated model data of the tool shank and holder.

Abstract: A numerically controlled machine tool has at least one movement axis and is connected to a numerical controller which includes a parts program. Movements of each movement axis are limited by maximum permissible axis dynamics. The parts program has a sequence of instructions for machining a workpiece which specify different maximum desired speeds for the machining of the workpiece which change abruptly over time. The numerical controller approximates the different maximum desired speeds which change abruptly over time with a desired speed profile that is continuous over time and has a profile of the maximum desired speeds which is also continuous over time. The numerical controller uses the continuous desired speed profile to calculate the desired values of an actual movement profile of the movements for each movement axis.

Abstract: A micro grid system comprises a secondary energy source and a power controller. The secondary energy source is associated with a micro grid that includes a fixed or mobile facility, and the secondary energy source is configured to generate first DC power signal. The power controller is in communication with the secondary energy source and an electric grid, and configured to receive first AC power signal from the electric grid and the first DC power signal from the secondary energy source and output a second AC power signal to loads in communication with the power controller. The power controller comprises an AC to DC frequency converter configured to change frequency and/or voltage of the second AC power signal, a processor, and a memory configured to store instructions that, when executed, cause the processor to control the frequency converter to change the frequency and/or voltage of the second AC power signal.