Abstract: A rapid material development process for a powder bed fusion additive manufacturing (PBF AM) process generally utilizes a computational fluid dynamics (CFD) simulation to facilitate selection of a simulated parameter set, which can then be used in a design of experiments (DOE) to generate an orthogonal parameter space to predict an ideal parameter set. The orthogonal parameter space defined by the DOE can then be used to generate a multitude of reduced volume build samples using PBF AM with varying laser or electron beam parameters and/or feedstock chemistries. The reduced volume build samples are mechanically characterized using high throughput techniques and analyzed to provide an optimal parameter set for a 3D article or a validation sample, which provides an increased understanding of the parameters and their independent and confounding effects on defects and microstructure.

Abstract: A measurement apparatus comprising at least one device interface adapted to connect an auxiliary measurement device and/or a device under test, DUT, to said measurement apparatus; a user interface adapted to input by a user settings for performing a measurement by said measurement apparatus and an artificial intelligence, AI, module adapted to provide current settings of said measurement apparatus, wherein said artificial intelligence, AI, module is machine learned on the basis of connected devices and/or settings during historic measurements performed by said measurement apparatus.

Abstract: Techniques for predicting an amount of at least one biomaterial produced or consumed by a biological system in a bioreactor are provided. Process conditions and metabolite concentrations are measured for the biological system as a function of time. Metabolic rates for the biological system, including specific consumption rates of metabolites and specific production rates of metabolites are determined. The process conditions and the metabolic rates are provided to a hybrid system model configured to predict production of the biomaterial. The hybrid system model includes a kinetic growth model configured to estimate cell growth as a function of time and a metabolic condition model based on metabolite specific consumption or secretion rates and select process conditions, wherein the metabolic condition model is configured to classify the biological system into a metabolic state. An amount of the biomaterial based on the hybrid system model is predicted.

Abstract: A method for detecting a slow node includes: obtaining a generated record for a first storage node, the generated record including a storage node generation time, and a number of times and consuming time for transmitting data to second storage nodes other than the first storage node; obtaining a valid record from the generated record, the valid record being generated within a preset time period, and the preset time period being within a time period between the storage node generation time and a current time; determining an average consuming time for the first storage node transmitting the data to each of the second storage nodes, based on the number of times and the consuming time in the valid record; and detecting the slow node in the second storage nodes based on the average consuming time.

Abstract: An acquisition unit (10) acquires normal sample data and non-normal sample data. A model generation unit (120) generates a normal model representing the normal sample data. A change unit (141) generates a non-normal feature vector of the non-normal sample data, and generates a non-normal changed vector obtained by changing an element of the non-normal feature vector. When the non-normal changed vector and the normal model are similar to each other, a verification unit (142) executes a process using sample data represented by the non-normal changed vector. The verification unit (142) verifies whether an anomalous event is detected by a detection device. Upon verification that an anomalous event is not detected, the verification unit (142) determines whether an anomalous event is present, independently of the detection device.

Abstract: An optimization method includes: identifying, for each of a plurality of replicas each of which has a plurality of state variables, an amount of change in strength of interaction that corresponds to a change in a distance between the replica and another replica in a state space in a case where a value of a first state variable among the plurality of state variables of the replica is updated, the state space indicating a space which a combination of values of the plurality of state variables is able to take; and determining whether or not to update the value of the first state variable, based on a proposal probability that corresponds to the amount of change in the strength of interaction in the case where the value of the first state variable is updated and based on an acceptance probability that corresponds to a target probability distribution.

Abstract: An I/O server service interacts with multiple containerized controller services each implementing the same control routine to control the same portion of the same plant. The I/O server service may provide the same controller inputs to each of the containerized controller services (e.g., representing measurements obtained by field devices and transmitted by the field devices to the I/O server service). Each containerized controller service executes the same control routine to generate a set of controller outputs. The I/O server service receives each set of controller outputs and forwards an “active” set to the appropriate field devices. The I/O server service and other services, such as an orchestrator service, may continuously evaluate performance and resource utilization in the control system, and may dynamically activate and deactivate controller services as appropriate.

Abstract: A computer-implemented method for creating a control process for a technical system using a Bayesian optimization method, the control process being created and executable based on model parameters of a control model, the following steps being performed in order to optimize the control process: furnishing a quality function that corresponds to a trainable regression function, and that assesses a quality of a control process of the technical system based on model parameters; executing a Bayesian optimization method based on the quality function in order to iteratively ascertain an optimized model parameter set having model parameters, such that during execution of the Bayesian optimization method, a model parameter domain that indicates the permissible value ranges for the model parameters is expanded, by an amount equal to an expansion distance, with respect to those dimensions for which the model parameter ascertained in the current iteration lies at a range boundary.

Abstract: The present disclosure provides a switch circuit and a control method thereof, a smart switch and a control system. The switch circuit includes a wireless communication module, a switch module coupled to a load, a switch-on power obtaining circuit, an energy storage circuit coupled with the wireless communication module and a switch-off power obtaining circuit. The load is coupled with a neutral wire. The switch-on power obtaining circuit is configured to output a first current to the energy storage circuit in response to the switch module being switched on. The switch-off power obtaining circuit is configured to output a second current to the energy storage circuit via the second power supply terminal in response to the switch module being switched off. The second current is less than the first current.

Abstract: An electronic apparatus including at least one interface; and at least one processor configured to: register a first user account with a first server configured to provide a first service, through the at least one interface, identify a second server corresponding to an external apparatus connectable through the at least one interface, wherein the second server is configured to provide a second service different from the first service, register the first user account with the second server through the at least one interface to link the first user account to a second user account corresponding to the second service, and perform a linkage service operation based on the first service and the second service, using the first user account and the second user account.

Abstract: The embodiments described herein include one embodiment that a control method including executing an infeasible search algorithm during a first portion of a predetermined sample period to search for a feasible control trajectory of a plurality of variables of a controlled process, executing a feasible search algorithm during a second portion of the predetermined sample period to determine the feasible control trajectory if the infeasible search algorithm does not determine a feasible control trajectory, and controlling the controlled process by application of the feasible control trajectory.

Abstract: A control device and a monitoring system of a manufacturing device, capable of enabling an external device to acquire data easily without grasping a configuration of the control device having a plurality of function control units. A control device of a manufacturing device includes a display function control unit and a control function control unit. The display function control unit includes a data model generation unit, and the control function control unit includes a data model generation unit. The display function control unit includes: a data model acquiring unit that acquires a data model generated by the data model generation unit of the control function control unit; and a data model integration unit that integrates a data model generated by the data model generation unit of the display function control unit with a data model of the control function control unit acquired by the data model acquiring unit.

Abstract: A compact data structure generation engine can be used to generate a compact data structure that represents performance data for high-scale networks. The compact data structure representing the performance data can be used to monitor the operation performed on or by a computer system to identify potentially anomalous conditions. In response, a corrective action can be taken to address the issue. This can be useful, for example, in improving the efficiency, effectiveness, and reliability of the computer system during operation.

Abstract: The present disclosure relates to a scalable experimental workflow that uses a culture system to maintain a steady state in a biological system, and techniques for identifying values for parameters in a in silico model based on experimental data obtained from the biological system. Particularly, aspects of the present disclosure are directed to obtaining measurement data for one or more characteristics of a biological system developed in a culture system, where the measurement data is indicative of each of the one or more characteristics at a physiological steady state where growth of the biological system is occurring at a substantially constant growth rate, determining a value for a parameter of a model of the biological system based on an growth formula, the measurement data, and the substantially constant growth rate, and parametrizing the model with at least the value determined for the parameter.

Abstract: A component mounting system includes multiple component mounting lines where multiple component mounters and a feeder storage are aligned along a board conveyance direction, a feeder exchange device configured to move along the board conveyance direction to exchange the feeder between the component mounter and the feeder storage of the component mounting line in charge, and a memory device. The feeder exchange device is configured to store an in-process feeder in the feeder storage of the component mounting line in charge, when it is determined, based on production information and feeder information, that there is the in-process feeder that was used in the component mounting line in charge and is scheduled to be used in another component mounting line.

Abstract: Disclosed herein are related to a system, a method, and a non-transitory computer readable storing instructions for operating an energy plant comprised of heating, ventilation and air conditioning (HVAC) devices. In one aspect, the system generates gradient data indicating a gradient of operating performance of the energy plant with respect to values of a plurality of control variables of HVAC devices. The system determines, from the plurality of control variables, a reduced group of control variables of the HVAC devices based on the gradient data. The system determines a set of values of the reduced group of control variables. The system operates the energy plant according to the determined set of values of the reduced group of control variables.

Abstract: An update system may be used to update referenced data objects that are used by multiple applications. In some cases incorrect data may be entered and later corrected. Data consistency techniques are described herein to help avoid use of incorrect data before the data is corrected. A communication from the update system may include updated master data objects and an indication that there are further updates queued. A flag may be set for each of the updated master data objects as they are stored in a database. Then when a request to access those objects is received, the request may be denied when the flag set, thereby preventing access to potentially incorrect or outdated data.

Abstract: A system includes a first asset disposed in an industrial environment configured to perform one or more operations, a second asset disposed in the industrial environment, and a server device communicatively coupled to the first asset and the second asset. The server device is configured to receive a first set of stream-based data from the first asset, receive a second set of stream-based data from the second asset, wherein the first set of stream-based data and the second set of stream-based data are received in real time or near real time, determine whether the one or more operations are within a threshold based on a comparison of the first set of stream-based data with respect to the second set of stream-based data, and send a command to the first asset or the second asset in response to the one or more operations being outside the threshold.

Abstract: A control device includes a processor that controls a printing manufacturing process including printing processing and post-processing in plural types of printing manufacture, in which the processor is configured to: according to an occurrence of an event in which the printing processing has ended but printing manufacture to be performed again is required, acquire information about a type of a sheet from printing manufacture information about printing manufacture having a delivery date; predict a time required for each processing of the printing manufacturing process in the printing manufacture; calculate an end time of reprinting manufacture, in which the printing manufacture to be performed again is required, in a case where the reprinting manufacture is incorporated so as to be continuous with other printing manufacture in which the same sheet as the reprinting manufacture is used; and perform control to determine whether or not to incorporate the reprinting manufacture so that the reprinting manufacture i

Abstract: An apparatus, methods and systems for data collection related to an oil and gas process and disclosed. A system may include a multi-sensor acquisition component including a plurality of inputs and a plurality of outputs, a sensor data storage profile circuit structured to determine a data storage profile including a data storage plan for the plurality of inputs, a sensor communication circuit structured to interpret a plurality of inputs, a sensor data storage implementation circuit structured to store at least a portion of the inputs in response to the data storage profile, a data analysis circuit structured to analyze the plurality of inputs and determine a data quality parameter, and a data response circuit structured to adjust at least one of the data storage profile and the data collection routine in response to the data quality parameter.

Abstract: A data center infrastructure monitoring system and method that includes a plurality of geographically distributed data centers, each data center comprising a plurality of mechanical assets. A data center gateway system communicatively coupled to one or more data centers of the plurality of data centers is configured to determine a subset of the plurality of mechanical assets of the data center that provide cooling to equipment of a customer of the data center, and output, for display, a graphical depiction of the subset of the plurality of mechanical assets of the data center that provide cooling to equipment of the customer in the data center.

Abstract: Techniques for operating a sensor are provided. An example method according to these techniques includes sensing, at the sensor, changes in intensity of a magnetic field of a magnet affixed to a monitored asset to produce sensor data, wherein the monitored asset is disposed in a non-metallic liquid or solid medium, and wherein the sensor is disposed outside of the non-metallic medium; The method also includes analyzing, at the sensor, the sensor data to produce feature information indicative of vibration of the monitored asset. The method also includes providing the feature information to a predictive algorithm to generate prognosis information indicating an occurrence of a known condition of the monitored asset.

Abstract: A system and method for controlling a drilling tool inside a wellbore makes use of simulated annealing and Bayesian optimization to determine optimum controllable drilling parameters. In some aspects, a computing device generates sampled exploration points using simulated annealing and runs a Bayesian optimization using a loss function and the exploration points to optimize at least one controllable drilling parameter to achieve a predicted value for a selected drilling parameter. In some examples, the selected drilling parameter is rate-of-penetration (ROP) and in some examples, the controllable drilling parameters include such parameters as rotational speed (RPM) and weight-on-bit (WOB). In some examples, the computing device applies the controllable drilling parameter(s) to the drilling tool to achieve the predicted value for the selected drilling parameter and provide real-time, closed-loop control and automation in drilling.

Abstract: Duty cycles of pulse width modulation (“PWM”) pulses are determined by measurements taken with respect to an internally generated clock signal. One of these measurements calculates, in a continuous dynamic manner, a ratio of the number of cycles of the internally generated clock signal to one or more cycles of a PWM clock signal utilized as a time base for generation of the PWM pulses. This clock ratio measurement designates how many cycles of the internally generated clock signal will be used to designate a first portion of a duty cycle for each PWM pulse. Another measurement is utilized to determine a fractional portion of a cycle of the internally generated clock signal that will be used to designate a second portion of the duty cycle for each PWM pulse.

Abstract: Systems, devices, and methods of measuring directional latency and congestion in a communication network. A Uni-Directional Latency Determination Unit is connected in a communication network, located between an end-user device and a server. It monitors packets transported between the end-user device and the server, and it estimates a uni-directional latency of packet transport from the end-user device to the server or from the server to the end-user device. It utilizes a Transmission Control Protocol (TCP) Header and Timestamp Analyzer, to perform an analysis of data contained in timestamps of TCP packet headers of transported packets; and particularly, it analyzes data contained in a TSval field of such TCP packet headers. Congestion mitigation operations are accordingly deployed or activated.

Abstract: In exemplary aspects of optimizing data centers, historical data corresponding to a data center is collected. The data center includes a plurality of systems. A data center representation is generated. The data center representation can be one or more of a schematic and a collection of data from among the historical data. The data center representation is encoded into a neural network model. The neural network model is trained using at least a portion of the historical data. The trained model is deployed using a first set of inputs, causing the model to generate one or more output values for managing or optimizing the data center with respect to design and risk aspects.

Abstract: A topology configuration system receives a graphic representation comprising object images of information handling systems to be configured for operating as a complex collection of information handling systems, uses artificial intelligence and deep learning to analyze images on the graphic representation and determine specific information handling systems present in the complex collection of information handling systems. A requirement list is used to create a configuration job. Sets of user instructions are sent to a user to guide the user and sets of device instructions are sent to each information handling system so that the user can configure the plurality of information handling systems to operate as the complex collection of information handling systems. Validation packets may be sent to each information handling system to confirm the complex collection of information handling systems is set up quickly and with little or no troubleshooting.

Abstract: A control method according to the present disclosure is executed by a first server of servers in a system including one or more IoT devices and the servers. The method includes: obtaining first transaction data including malfunction information indicating that one of the IoT devices is malfunctioning, and time information indicating a time when the IoT device has obtained the malfunction information; transferring the obtained first transaction data to second servers different from the first server; executing, together with the second servers, a first consensus algorithm for an agreement on an authenticity of the first transaction data; and recording a block containing the first transaction data in a distributed ledger of the first server, when the authenticity of the first transaction data is verified by the first consensus algorithm.

Abstract: Techniques for predicting an amount of at least one biomaterial produced or consumed by a biological system in a bioreactor are provided. Process conditions and metabolite concentrations are measured for the biological system as a function of time. Metabolic rates for the biological system, including specific consumption rates of metabolites and specific production rates of metabolites are determined. The process conditions and the metabolic rates are provided to a hybrid system model configured to predict production of the biomaterial. The hybrid system model includes a kinetic growth model configured to estimate cell growth as a function of time and a metabolic condition model based on metabolite specific consumption or secretion rates and select process conditions, wherein the metabolic condition model is configured to classify the biological system into a metabolic state. An amount of the biomaterial based on the hybrid system model is predicted.

Abstract: Systems and methods for determining operation commands for a fixture within an area of a facility. One example system includes a processor configured to: receive, from a first fixture associated with an area within a facility, operational data related to an operation of the first fixture; receive, from a second fixture associated with the area within the facility, environmental data related to a condition of the area; process the operational data and the environmental data through a status model to determine a status for the area, the status model trained with operational data and environmental data previously received from the first fixture, the second fixture, and other fixtures associated with the facility; determine an operation command for a third fixture associated with the area within the facility based on the status; and provide the operation command to the third fixture for execution.

Abstract: A generator set monitoring and control system includes a generator set located in a first location, an on-site controller located near the first location, and a remote display, located in a second location. The remote display is configured to send instructions to at least one of the generator set and on-site controller, receive genset operation outputs from the on-site controller, and display genset operation outputs.

Abstract: Embodiments for using a mixed internet of things (IoT) device network to improve user satisfaction by a processor. A collaboration of data associated with a user captured from a plurality of types of IoT devices in the IoT network may be gathered. The collaboration of data may be used to determine a level of satisfaction of the user according to a knowledge domain describing a plurality of satisfaction factors and levels in the service based industry such that the collaboration of data is associated with one or more of the plurality of satisfaction factors and levels.

Abstract: Example implementations relate to calculating a weighted efficiency index. An example implementation includes fetching a public resource utilization metric and a public cloud resources cost. A private resource utilization metric is collected and a private cloud resources cost is calculated. A weighted efficiency index is calculated from the public cloud resources cost, the private cloud resources cost, or any combination thereof, and a weighted deviation from an ideal resource utilization percentage. The weighted efficiency index may be displayed on a user interface.

Abstract: Configuring distributed control in an industrial system comprises building an asset model representative of a process control installation of the industrial system and creating an asset library of distributed control assets according to a distributed control programming standard. The asset model includes modeled assets defined according to levels of a physical model standard and representing physical devices of the industrial system. The distributed control assets each have one or more predefined, built-in facets. One of the distributed control assets in the asset library is mapped to each of the modeled assets to configure the process control installation of the industrial system and generate an asset-based control application for providing distributed control of the industrial system. Additional aspects relate to auto-creation of control applications based on an information model, either through the use of machine learning or an asset configurator tool.

Abstract: The present disclosure relates to systems and methods that use computer-vision processing systems to improve patient safety during surgical procedures. Computer-vision processing systems may train machine-learning models using machine-learning techniques. The machine-learning techniques can be executed to train the machine-learning models to recognize, classify, and interpret objects within a live video feed. Certain embodiments of the present disclosure can control (or facilitate control of) surgical tools during surgical procedures using the trained machine-learning models.

Abstract: A method includes obtaining operating data associated with operation of a cross-directional industrial process controlled by at least one model-based process controller. The method also includes, during a training period, performing closed-loop model identification with a first portion of the operating data to identify multiple sets of first spatial and temporal models. The method further includes identifying clusters associated with parameter values of the first spatial and temporal models. The method also includes, during a testing period, performing closed-loop model identification with a second portion of the operating data to identify second spatial and temporal models. The method further includes determining whether at least one parameter value of at least one of the second spatial and temporal models falls outside at least one of the clusters.

Abstract: A renewable power plant configured to deliver electrical power to an electrical grid in accordance with a reference is disclosed. The renewable power plant comprises at least one energy generating system of a first type, at least one energy generating system of a second type, and a control system including a central power plant controller (CPPC) which generates setpoints for controlling the energy generating systems in accordance with the reference. The energy generating systems provide feedback signals to the CPPC. The control system is configured to generate a modified feedback signal based on the feedback signal received from the energy generating systems of the second type, and using a model representing operational behavior of the energy generating systems of the second type. The CPPC is configured to apply the modified feedback signal to a feedback control loop for controlling the energy generating systems.

Abstract: Techniques for detecting physical conditions at a physical premises from collection of sensor information from plural sensors execute one or more unsupervised learning models to continually analyze the collected sensor information to produce operational states of sensor information, produce sequences of state transitions, detect during the continual analysis of sensor data that one or more of the sequences of state transitions is a drift sequence, correlate determined drift state sequence to a stored determined condition at the premises, and generate an alert based on the determined condition. Various uses are described for these techniques.

Abstract: A determination apparatus extracts a plurality of specific events that have values greater than an event determination threshold from among a plurality of events that have occurred in chronological order. The determination apparatus generates a feature amount related to adjacent occurrence intervals of the plurality of specific events, using the plurality of specific events. The determination apparatus generates array data corresponding to the plurality of events using points each having components of the event determination threshold and the feature amount, while changing the event determination threshold. The determination apparatus determines a type of the plurality of events using the array data.

Abstract: A data-based nuclear power plant design basis management system and a method therefor are disclosed. According to an embodiment of the present invention, the data-based nuclear power plant design basis management system comprises a database for storing: information on a plurality of design basis for defining a design basis document for configuration management in a nuclear power plant; information on a category, corresponding to each of the design basis, among a plurality of categories; and an associative relationship between the plurality of design basis, wherein the plurality of categories includes design requirements (REQ), at least one design basis specification (DBS) for satisfying the REQ, and the like.

Abstract: In an exemplary embodiment, software made in accordance with the present invention displays a marketplace interface, which displays at least a portion of a CAD model and a set of marketplace tool selectors to a user such that the user can manipulate the tool selectors to interact with an electronic marketplace. The marketplace interface may include a spectrum interface designed and configured to allow the user to selectively augment the marketplace interface with additional functionality. Various corresponding and related systems, methods, and software are described.

Abstract: An extremum seeking controller includes a processing circuit configured to modulate a manipulated variable provided as an input to a plant using an extremum-seeking control technique to drive a gradient of an objective function with respect to the manipulated variable toward an extremum. The objective function includes a performance variable characterizing a performance of the plant responsive to the manipulated variable. The objective function also includes a saturation adjustment term that becomes active as the plant approaches a saturation point and remains active as the plant operates within a saturated region past the saturation point. The saturation adjustment term causes the processing circuit to adjust the manipulated variable toward a value of the manipulated variable that returns the plant from the saturated region to a non-saturated region.

Abstract: Systems, methods, techniques and apparatuses of power network control are disclosed. One exemplary embodiment is a power network comprising a plurality of zones each including a plurality of measurement devices structured to measure electrical characteristics of the corresponding zone, a zone controller structured to receive measurements from the plurality of measurement devices, a distributed energy resource (DER), and a load. Each zone controller is structured to receive a set of local measurements from the plurality of measurement devices of the corresponding zone, calculate a sensitivity matrix using the received set of local measurements, determine whether a voltage violation has occurred in the corresponding zone, determine a DER set point using the received set of local measurements in response to determining the voltage violation has occurred in the corresponding zone, and transmit the DER set point to the DER.

Abstract: According to an aspect, there is provided method for commissioning a drive. First, a local network is established between a wireless computing device, one or more wireless sensor devices and a drive. Each wireless sensor device is configured to measure one or more physical quantities associated with an industrial system controlled by the drive. The wireless computing device configures wirelessly the drive and the one or more wireless sensor devices for performing measurements. In response to receiving one or more measured values from the one or more wireless sensor devices, the wireless computing device displays the information on the one or more measured values on a display for providing guidance for a user of the wireless computing device for adjusting drive parameters of the drive.

Abstract: A monitoring system for data collection related to a production line of an industrial environment includes a data storage structured to store a plurality of data collection templates, each of the plurality of data collection templates comprising a data collection routine; a data collector structured to interpret a plurality of detection values that correspond to a plurality of input channels, wherein the plurality of detection values are obtained according to a data collection routine corresponding to a selected one of the plurality of data collection templates; wherein the data storage is further structured to store at least a portion of the plurality of detection values; a data analysis circuit structured to interpret at least a subset of the detection values to determine a state value corresponding to one of a process or a component of the production line; and an expert system circuit structured to perform a data collection modification by performing one of: adjusting the data collection routine correspond

Abstract: A method for operating an automation system comprising at least one field device associated to a local control device is provided. The method comprises: controlling an operation of the field device based on control data generated by the local control device; receiving monitoring data describing the controlled operation of the field device from the field device; modifying configuration data of the local control device based on the monitoring data; generating upload data comprising information about the modification of the configuration data and/or about changes in the operation of the field device resulting from the modification of the configuration data; in the local control device and/or in a central control device, deleting, encrypting and/or masking specified information from the upload data to generate modified upload data; and providing the modified upload data for use by another local control device.

Abstract: Provided are energy device control systems for distributed grid subsystem that control a first power demand of a plurality of appliances. The control system comprises a graphical user interface configured to accept a user input indicative of a first demand and dynamic allocation flexibility associated with the a respective energy device; a communication interface configured to aggregate dynamic allocation values from a plurality of system nodes including at least the user input indicative of a first demand and the dynamic allocation flexibility; and at least one processor programmed to: generate a learning model for evaluating dynamic future allocation with future energy execution prediction, wherein the dynamic future allocation includes at least energy operational information based on a categorization of energy usage at a plurality of respective energy devices; and trigger energy generation on the energy grid at respective generator nodes according to the learning model and dynamic projections.

Abstract: An information processing device includes: a memory; and a processor configured to: hold each of values of state variables included in an evaluation function representing energy; calculate the change value of the energy for each of state transitions, when a state transition occurs due to a change of any of the values of the state variables; control a temperature value representing temperature; select any of the state transitions, based on priority information set based on state transition information updated last time with respect to identification information for identifying each state transition, and transition acceptance information indicating transition acceptance determined based on the change value, and a generated thermal noise; and output a lowest energy state which is the values of the state variables when the energy to be updated based on the selected state transition becomes a lowest value.

Abstract: An apparatus, methods and systems for data collection in an industrial environment are disclosed. A monitoring system can include a data collector coupled to a plurality of analog sensors to collect data, a data storage structured to store a plurality of data collection management plans comprising template data collection routines for collection of data, a data acquisition circuit structured to interpret a plurality of detection values from the collected data, and a data analysis circuit structured to analyze the collected data and select one of the plurality of data collection management plans, wherein the selected one of the plurality of data collection management plans is selected is at least in part based on a data analysis of received data from the plurality of analog sensors.

Abstract: An error compensation system for a numerical control (NC) machine tool based on iterative learning control, including a trajectory generating module, a down-sampling module, a position controller, a first holder, a velocity-loop iterative learning controller, a velocity controller, a second holder and a control plant. The trajectory generating module is configured to generate a desired trajectory command including a first sampling command. The first sampling command is transmitted to the down-sampling module and the velocity-loop iterative learning controller. The first sampling command is down-sampled through the down-sampling module to obtain a second sampling command. The velocity-loop iterative learning controller is configured to receive the first sampling command, and obtain a first sampling error compensation sequence according to a first sampling error sequence and a first sampling error compensation sequence of a previous iteration machining process stored therein.