Abstract: The present application discloses a chance constrained extreme learning machine method for nonparametric interval forecasting of wind power, which belongs to the field of renewable energy generation forecasting. The method combines an extreme learning machine with a chance constrained optimization model, ensures that the interval coverage probability is no less than the confidence level by chance constraint, and takes minimizing the interval width as the training objective. The method avoids relying on the probability distribution hypothesis or limiting the interval boundary quantile level, so as to directly construct prediction intervals with well reliability and sharpness. The present application also proposes a bisection search algorithm based on difference of convex functions optimization to achieve efficient training for the chance constrained extreme learning machine.

Abstract: Systems and methods are provided for optimizing predictions regarding traffic conditions based upon learned/measured traffic conditions. Current traffic conditions can be measured and characterized based on speed or other factors as a vehicle traverses the route. These measured traffic conditions can be compared to predicted traffic conditions. A weighting term can be associated with the measured traffic conditions based upon the comparison. During a subsequent time that the vehicle traverses the route, a traffic conditions prediction may be made. The weighting term and measured traffic conditions data can be used to adjust the traffic conditions prediction for better accuracy, and an optimal time(s) during which a battery of a hybrid vehicle can be pre-charged can be requested.

Abstract: Systems and methods for improving recordkeeping and analysis of an asset include creating and maintaining an integrated record about the asset. In some embodiments, the systems and methods include collecting data about an asset to form an asset data collection, recording the asset data collection in a record, analyzing at least a portion of the asset data collection to determine a characteristic of the asset, and recording the characteristic of the asset in the record. In some embodiments, recording the characteristic in the record includes adding the characteristic to the asset data collection.

Abstract: A method for performing a task in registration with a discrete seal in at least one material is described herein. The method involves simultaneously forming a discrete seal and a fiducial/eye mark in the at least one material. The method includes providing a detection device; providing a unit operation mechanism; and performing an operation on the material(s) in registration with the discrete seal. The task performed in registration with the discrete seal is based upon the location of the eye mark that was simultaneously formed with the discrete seal. A method of making flexible containers using cutting to form the outer periphery of the packages is described herein. Also described herein are flexible containers and container blanks made by such a method.

Abstract: In a system and method for supervisory management of fluid pipeline/LNG plant/gas plant/refinery/offshore oil and gas platform allowing simultaneous execution of commands at all control points, significantly increasing the speed at which an optimal set-point can be achieved in comparison to manual entry of commands. The pipeline/LNG plant/gas plant/refinery/offshore oil and gas platform control system has a cascade control configuration that can operate in conjunction with existing pipeline/LNG plant/gas plant/refinery/offshore oil and gas platform protection systems. The control room operator can activate automatic operation via the supervisory management system, and can subsequently command that the system switch back to manual control instantaneously. Dynamic models predict operating conditions of pipeline/LNG plant/gas plant/refinery/offshore oil and gas platform processes subject to constraints on pressure and other operating parameters.

Abstract: Acquiring and evaluating data regarding the performance of critical equipment of various business units distributed around the globe is essential in today's market. In particular aggregating, organizing and evaluating various types of data at a host processing system that is accessible via an intuitive graphical user interface to approved users connected to an enterprise network.

Abstract: Implementations described herein generally relate to a method for detecting anomalies in time-series traces received from sensors of manufacturing tools. A server feeds a set of training time-series traces to a neural network configured to derive a model of the training time-series traces that minimizes reconstruction error of the training time-series traces. The server extracts a set of input time-series traces from one or more sensors associated with one or more manufacturing tools configured to produce a silicon substrate. The server feeds the set of input time-series traces to the trained neural network to produce a set of output time series traces reconstructed based on the model. The server calculates a mean square error between a first input time series trace of the set of input time series traces and a corresponding first output time series trace of the set of output time-series traces.

Abstract: Systems and methods of a Hierarchical Smart Asset Control Application development and Integrated Smart Asset Control System optimization are disclosed. In various embodiments, the system may develop a Hierarchical Asset Control Application and corresponding control hardware requirements. This can be used to create an Integrated Smart Asset Control System in order execute various processes for a set of equipment elements. The smart assets associated with the system may utilize intelligent agents to balance operational constraints and operational objects in order to determine real-time optimized operational parameters for a process and implement the appropriate controls to facilitate achieving the improved operational objectives.

Abstract: Embodiments are directed to managing visualizations. Visualizations based on data from a data source may be provided. Assessment models based on the visualizations may be provided such that the assessment models may detect mirages in the visualizations. Assessment models may be employed to determine Assessment results based on the visualizations and the data from the data source such that each assessment result includes an assessment score that corresponds to a detection of mirages. Assessment results may be rank ordered based on the assessment score. A report may be provided that includes the rank ordered list of the assessment results.

Abstract: A method and associated system, includes implementing a controller, configured to communicate, over a communication network, with a plurality of highly-versatile field devices coupled to the controller. The method and system also include configuring the network to facilitate communication of traffic over an advanced physical layer (APL) medium. One or more APL power switches are configured to provide connectivity to other devices and each includes a power supply to provide power via the medium. One or more APL field switches, each receiving power from a power switch, are configured to distribute both communication signals and power signals to field devices communicatively coupled to a respective field switch.

Abstract: A system including a deep learning processor receives one or more control signals from one or more of a factory's process, equipment and control (P/E/C) systems during a manufacturing process. The processor generates expected response data and expected behavioral pattern data for the control signals. The processor receives production response data from the one or more of the factory's P/E/C systems and generates production behavioral pattern data for the production response data. The process compares at least one of: the production response data to the expected response data, and the production behavioral pattern data to the expected behavioral pattern data to detect anomalous activity. As a result of detecting anomalous activity, the processor performs one or more operations to provide notice or cause one or more of the factory's P/E/C systems to address the anomalous activity.

Abstract: A computing system may include a virtual cross metrology engine configured to construct a given virtual metrology model. The given virtual metrology model may take, as inputs, process parameters applied for the given step of a semiconductor fabrication process. The virtual cross metrology engine may also be configured to construct a subsequent virtual metrology model, and the subsequent step is performed after the given step in the semiconductor fabrication process. Doing so may include determining inputs for the subsequent virtual metrology model from a combination of the process parameters applied for the given step of the semiconductor fabrication process, process parameters applied for the subsequent step of the semiconductor fabrication process, and a wafer value for the given step of the semiconductor fabrication process that the given virtual metrology model is configured to predict.

Abstract: In one embodiment, a wizard can automate a setup of a welding simulation by requiring the input of data (e.g. in data entry fields labelled as required) that is used to automatically set up a welding simulation. The wizard can be part of a general purpose mechanical simulation software package, and the wizard can receive inputs from CAD software that specifies the geometrical shapes of bodies of the assembly to be welded and the filling material itself and physical properties of bodies to be welded (e.g. sizes of bodies, number of bodies, physical arrangement and geometries of bodies, melting temperatures, etc.), in addition to the material physical properties and the wizard can provide outputs to the mechanical simulation software package to provide boundary conditions for use in the mechanical simulation software that can use finite element analysis methods in simulations.

Abstract: Implementations described herein generally relate to a method for detecting anomalies in time-series traces received from sensors of manufacturing tools. A server feeds a set of training time-series traces to a neural network configured to derive a model of the training time-series traces that minimizes reconstruction error of the training time-series traces. The server extracts a set of input time-series traces from one or more sensors associated with one or more manufacturing tools configured to produce a silicon substrate. The server feeds the set of input time-series traces to the trained neural network to produce a set of output time series traces reconstructed based on the model. The server calculates a mean square error between a first input time series trace of the set of input time series traces and a corresponding first output time series trace of the set of output time-series traces.

Abstract: A method and associated system, includes implementing a controller, configured to communicate, over a communication network, with a plurality of highly-versatile field devices coupled to the controller. The method and system also include configuring the network to facilitate communication of traffic over an advanced physical layer (APL) medium. One or more APL power switches are configured to provide connectivity to other devices and each includes a power supply to provide power via the medium. One or more APL field switches, each receiving power from a power switch, are configured to distribute both communication signals and power signals to field devices communicatively coupled to a respective field switch.

Abstract: Cybersecurity is enhanced to detect credential spray attacks. Accounts with access failure events are divided into buckets B1 . . . BN based on access failure count ranges R1 . . . RN. For instance, accounts with one logon failure may go in B1, accounts with two failures in B2, etc. Buckets will thus have account involvement extents E1 . . . EN, which are compared to thresholds T1 . . . TN. An intrusion detection tool generates an alert when some Ei hits its Ti. Detection may spot any credential sprays, not merely password sprays. False positives may be reduced by excluding items from consideration, such as logon attempts using old passwords. False positives and false negatives may be balanced by tuning threshold parameters. Breached accounts may be found. Detection may also permit other responses, such as attack disruption, harm mitigation, and attacker identification. Credential spray attack detection may be combined with other security mechanisms for defense in depth of cloud and other network accounts.

Abstract: A system that is a target of health monitoring via a computational system, the computational system, and corresponding method for determining health indicators using rank correlation analysis are disclosed. The target system includes a computational system that includes a computing device that acquires data from the target system, generate at least two features from the data acquired from the target system, computes, for each feature, rank correlation of the feature with time, computes the absolute value of each rank correlation coefficient for each feature, confining the range of the absolute value rank correlation coefficients to that from 0 to 1; and chooses at least one feature with a higher relative absolute value rank correlation coefficient as a health or condition indicator for the target system. The target system or the computational system or the method may perform health or condition monitoring on the target system.

Abstract: Acquiring and evaluating data regarding the performance of critical equipment of various business units distributed around the globe is essential in today's market. In particular aggregating, organizing and evaluating various types of data at a host processing system that is accessible via an intuitive graphical user interface to approved users connected to an enterprise network.

Abstract: Embodiments of the present invention provide control solutions for data center thermal management and control using an IDEC system. The data center is arranged in a cold air room wall supply and hot air room wall return configuration. The sensors, such as temperature sensors and/or pressure sensors, are utilized to measure and record thermal data. The data is then processed and used to control the IDEC system to adjust operating conditions to satisfy dynamic thermal requirements of the data center. The control functions include: 1) controlling the IDEC system to adjust cooling modes and operating conditions as needed to maintain proper data center thermal environment; and 2) identifying different optimal operating conditions and parameters for the IT room and IDEC system.

Abstract: A method of facilitating modeling of a system includes receiving, at a processor, an extensible markup language (XML) file corresponding to a piping and instrumentation diagram (PID) of the system; identifying, by the processor, components of the system that are described in the XML file, the XML file including information about attributes of the identified components; storing, by the processor, the information about the attributes of the identified components; and generating, by the processor, a simulation model page using syntax of a simulation modeling software environment, based on the stored information about the attributes of the identified components.

Abstract: A plant asset management system and method for managing field devices in a plant are implemented by association between control loop and plant asset value. One or more control loop configurations are extracted from one or more control system definitions of a process control system. One or more device configurations are extracted from one or more device management system definitions of a device management system. There is automatically determined whether one or more control loops and one or more devices are respectively associated with each other, based on the one or more loop configurations and the one or more device configurations.

Abstract: The present invention relates to numerical controller having a function for collecting the data regarding machining without using external devices such as data logger and outputting the data in batch.

Abstract: In one aspect, a system for identifying a root cause of a performance issue in a monitored entity is disclosed. The system can detect a performance issue with the monitored entity running in a monitored environment of networked entities; receive a plurality of datatypes and associated data for each entity, the plurality of datatypes include metrics, events, logs, snapshots, and configurations; provide a dashboard user interface to display the datatypes and associated data for each entity as user selectable items; receive user input through the dashboard user interface that indicate a selection of two of the datatypes for performing correlation analysis; perform the correlation analysis using the received user selection of the two of the datatypes; identify a candidate root cause of the performance issue based on the correlation analysis; and display the identified candidate root cause through the dashboard user interface.

Abstract: The invention relates to managing a plurality of subsystems of a process plant. The process plant is controlled using a Distributed Control System (DCS) with a plurality of databases distributed within the process plant, wherein each database comprises information corresponding to at least one subsystem of the plurality of subsystems. The method comprises receiving a query at a human machine interface of the DCS, wherein the query is of a predetermined type and is associated with at least one of an operation and health of a subsystem. The method further comprises identifying at a server of the DCS, a database comprising information corresponding to the subsystem. Furthermore, the method comprises processing the query based on the information corresponding to the subsystem. In addition, the method comprises utilizing the DCS to control the operation of the subsystem by controlling process parameters of the process in one or more subsystems.

Abstract: Methods and apparatus associated with data cold storage are described. Example apparatus include an array of data storage devices arranged in rows and columns. Columns of the array are orthogonal to rows. A row has an associated row-centric power supply, and a column has an associated column-centric local electronics module (LEM) that controls a data storage device in the column independently of other data storage devices in the array. Example apparatus include logics that control a power mode of a data storage device independently of other data storage devices in the array, that control a power mode of an LEM, that adaptively regulate the level of data stored in a buffer, and that determine whether a data object will be stored in the buffer or stored on a data storage device in the array, based on the probability the data object will be accessed within a threshold period of time.

Abstract: A method and an information handling system (IHS) determine optimum ambient temperature conditions for targeting desired system cooling constraints. According to one aspect, a target parameter recommendation module (TPRM) receives a target cooling parameter value for a number of servers having an identified configuration. The TPRM identifies an acceptable range of ambient conditions, corresponding to the received target parameter value(s). The TPRM determines via a series of iterations whether the target parameter value is attainable using the acceptable range of ambient conditions. If the target parameter value is attainable, the TPRM provides a first notification identifying ambient conditions by which the target parameter value can be attained. However, if the target parameter value is not attainable using the acceptable range of ambient conditions, the TPRM provides a second notification recommending an adjustment to server cooling constraints and/or the identified system configuration.

Abstract: Techniques are described for modeling variations in correlation to facilitate analytic operations. In one or more embodiments, at least one computing device receives first metric data that tracks a first metric for a first target resource and second metric data that tracks a second metric for a second target resource. In response to receiving the first metric data and the second metric data, the at least one computing device generates a time-series of correlation values that tracks correlation between the first metric and the second metric over time. Based at least in part on the time-series of correlation data, an expected correlation is determined and compared to an observed correlation. If the observed correlation falls outside of a threshold range or otherwise does not satisfy the expected correlation, then an alert and/or other output may be generated.

Abstract: Embodiments of the invention generally relate to wind turbine generators, and more specifically to the deactivation of wind turbines in a wind turbine park. A wind park controller may be configured to retrieve data indicating fatigue experienced by each wind turbine of the wind turbine park, and deactivate those turbines determined to be the most fatigued, thereby increasing the lifetime of turbines in the wind turbine park.

Abstract: A system and method of multi-agent reinforcement learning for integrated and networked adaptive traffic controllers (MARLIN-ATC). Agents linked to traffic signals generate control actions for an optimal control policy based on traffic conditions at the intersection and one or more other intersections. The agent provides a control action considering the control policy for the intersection and one or more neighboring intersections. Due to the cascading effect of the system, each agent implicitly considers the whole traffic environment, which results in an overall optimized control policy.

Abstract: Discussed herein are embodiments of methods and systems which allow engineers or administrators to create modular plugins which represent the logic for various fault detection tests that can be performed on data pipelines and shared among different software deployments. In some cases, the modular plugins each define a particular test to be executed against data received from the pipeline in addition to one or more configuration points. The configuration points represent configurable arguments, such as variables and/or functions, referenced by the instructions which implement the tests and that can be set according to the specific operation environment of the monitored pipeline.

Abstract: Among other things, one or more techniques and/or systems are provided for facilitating development, by a user, of a model describing a condition of an industrial asset. An output parameter of the model can be defined within a model development environment. The output parameter describes a condition of the industrial asset and can be defined using one or more variables. During deployment of the model within a deployment environment, respective variables of the model can be mapped to a data store where data associated with the variable is located. In this way, during development, a user can specify variables to be used within the model without specifying where to fetch and/or push data associated with the variable, for example. Further, the model can be executed within the deployment environment to assess the condition for a plurality of industrial assets.

Abstract: The embodiments described herein include a system and a method. In one embodiment, a system includes an industrial controller configured to control a first field device. The first field device includes an actuator and a positioner coupled to the actuator. The positioner is configured to position the actuator. The first field device is configured to detect an undesired condition and to communicate the undesired condition to the industrial controller by using a ReadBack facility of the first field device.

Abstract: A method for dynamically altering manufacturing routings to add, remove, or skip operations and combinations of operations within a shop floor control system in real-time to respond to current conditions. One aspect of the present invention is a computer-implemented method for dynamically generating a manufacturing production work flow. One embodiment of this method comprises receiving indication that an assembly has completed a manufacturing operation, the assembly having a work flow and a sampling strategy associated therewith; querying a data source for characteristics of a plurality of previously sampled components; querying a manufacturing floor control system for current production status; and dynamically updating the work flow for the assembly based at least in part on the sampling strategy, characteristics of the plurality of previously sampled components, and the current production status.

Abstract: This invention provides a system and method of Advanced Process Control for optimal operation of multi-unit plants in large scale processing and power generation industries. The invention framework includes the following components: continuous real time dynamic process simulation, automatic coefficient adjustment of dynamic and static process models, automatic construction of transfer functions, determination of globally optimal operating point specific to current conditions, provision of additional optimal operating scenarios through a variety of unit combinations, and calculation of operational forecasts in accordance with planned production.

Abstract: The present disclosure relates to a process tool system that utilizes tool sensor data and an embedded or built-in tool model to facilitate semiconductor fabrication. The process tool system includes a sensor data component, the tool model, and an execution system. The sensor data component is configured to provide the tool sensor data. The tool model is built in a process tool and is configured to generate model outputs based on model inputs. The manufacturing execution system is configured to provide tool process data, including actual metrology and previous process data, to the sensor data component. Additionally, the execution system provides the model inputs to the tool model and receives the model outputs from the tool model. The execution system provides one or more execution system outputs based on the sensor data and the model outputs. The sensor data can include measured semiconductor device characteristics.

Abstract: A wafer fabrication outcome, such as wafer yield or wafer lifetime, is predicted by excluding uncontrollable but measurable internal/external noises of a DOE system, and by rendering relations between wafer design variables and wafer outcome outputs to be more causal, as well as the relations between variances for each of the wafer design variables and the wafer outcome outputs. With the aid of a wafer fabrication outcome predicting model formed by the more causal relations, precision of predicting wafer outcomes can be raised, and performance of wafer fabrication can be thus raised as a result.

Abstract: A system for resource usage optimization employs an automatically controlled sensor suite providing data to a computer system for the analysis of spatial relationships of the sensors and resources. A control module incorporates an interactive logic, in an exemplary embodiment of well-stream coupled dynamic or game theory engines, operating in conjunction with the spatial data processing algorithms, GIS in an exemplary embodiment, receives as an input an objective function set for the use of the resource and constraint sets which are then monitored by the sensor suite. Incoming data is compared to the constraint sets and upon impact to any of the elements of the objective function set, creates a report/alarm for action or to trigger a corrective action.

Abstract: A method, apparatus, and machine readable storage medium is disclosed for managing a communication network wherein statistics are collected and next expected values for the statistics are calculated based on batch mean and confidence interval calculations and an alarm is raised if the next expected value exceeds a threshold.

Abstract: A computer-implemented integrated expert system for the identification of abnormal events in an industrial plant. The expert system integrates a model-based expert system with a rule-based expert system. The model-based expert system receives data on the operating conditions of a process unit in the industrial plant and calculates one or more results that determine whether the process unit is operating abnormally. The rule-based expert system also receives data on the operating conditions of the process unit and applies its rules to the process data. The rule-based expert system also applies its rules to the one or more results generated by the model-based expert system. The integrated system may also suppress any redundant messages generated by the model-based expert system.

Abstract: An output module for an industrial controller configurable to simplify setup and commissioning is disclosed. The output module includes configurable PWM outputs that may be scheduled to start at different times within the PWM period, that may be configured to generate a fixed number of PWM pulses, and that may have an extendable PWM period. The output terminals are configurable to enter a first state upon generation of a fault and further configurable to enter a second state after a configurable time delay following the fault being generated. The output module may receive inputs signals directly from another module and set output signals at the terminals responsive to these signals.

Abstract: The present disclosure includes a method for quantifying contribution to overall variability of moisture content in wood products and associated computer software. The method comprises the steps of obtaining moisture content data for the wood products and identifying one or more sources of variability in the moisture content data. A contribution to overall variability from each of the one or more sources of variability is then quantified. One or more opportunities to impact the overall variability are then quantified, each of the one or more opportunities being associated with one or more executable steps.

Abstract: A method for maintaining a technical plant including several components is provided. The method provides a system for planning the use of an enterprise resources system and a control system, with the enterprise resource system connected to the control system and structures of the technical plant are automatically set up in the enterprise resource system.

Abstract: Provided is a substrate processing system, which comprises a plurality of substrate processing apparatuses configured to process a substrate; and a group management apparatus configured to connect and manage the plurality of substrate processing apparatuses, wherein the group management apparatus includes: a communication part configured to transmit and receive data to and from the plurality of substrate processing apparatuses; a first storage part configured to store the data transmitted through the communication part from the plurality of substrate processing apparatuses; a second storage part configured to store a file prescribing a condition for determining an abnormality of the plurality of substrate processing apparatuses from the data; a display part including a manipulation screen for inputting the condition for determining the abnormality using the data stored in the first storage part or the file stored in the second storage part; a screen control part configured to control the display part to chang

Abstract: System and method for managing fermentation feed in a biofuel production process, comprising a dynamic multivariate predictive model-based controller coupled to a dynamic multivariate predictive model. The model is executable to: receive process information, including water inventory and biomass information, from the biofuel production process; receive a specified objective for the fermentation feed specifying a target biomass concentration; and generate model output comprising target values for a plurality of manipulated variables of the biofuel production process, including target flow rates of water and/or biomass contributing to the fermentation feed in accordance with the specified objective.

Abstract: A computer assisted method to monitor a status from a secondary location of a plurality of equipment on a drilling site, while simultaneously enabling preventive maintenance is described herein. A user can view at least one cycle, at least one control state, and at least one pressure. The user can also view equipment information, equipment repair history, and other information necessary to ensure that a piece of equipment has minimal down time.

Abstract: A method to monitor a status from a secondary location of a plurality of equipment on a drilling site, while simultaneously enabling preventive maintenance for the plurality of equipment is described herein. A user can view at least one cycle, at least one control state, and at least one pressure. The user can also view equipment information, equipment repair history, and other information necessary to ensure that a piece of equipment has minimal down time.

Abstract: A system to monitor a status from a secondary location of a plurality of equipment on a drilling site, while simultaneously enabling preventive maintenance is described herein. A user can view at least one cycle, at least one control state, and at least one pressure. The user can also view equipment information, equipment repair history, and other information necessary to ensure that a piece of equipment has minimal down time.

Abstract: Feedback is received from a plurality of devices. External data is also received. Statistical patterns of the plurality of devices are determined based on the feedback. A policy is determined based on the statistical patterns, the feedback, and the external data. The policy may include a set of rules dictating the operation of each of the plurality of devices and reducing energy consumption at the plurality of devices. Control data based on the policy is transmitted to the plurality of devices. The control data may be operative to transform the operation of the plurality of devices according to the set of rules.

Abstract: A building management strategy includes using exponentially weighted moving averages with statistical models to detect changes in the behavior of the building management system. Detected changes in the behavior of the system may indicate a detected fault, a change in a predicted behavior, or a need for the statistical models to be updated.

Abstract: Systems and methods for target optimization using regression are described. The system includes a regression subsystem to generate a function based on metric relationships, and an optimization subsystem to determine parameter values associated with an optimized target. Other embodiments may be described and claimed.