Abstract: Systems and methods for energy optimization of an HVAC system of a building are disclosed. The method includes collecting data from field sensors, the data including damper positions of a plurality of air handling units; calculating an aggregated ventilation rate for the air handling units based on the damper positions; retrieving a predictive model that outputs a predicted state for a plurality of building zones; inputting the damper positions to the predictive model; retrieving a baseline model that outputs an expected energy cost for a reporting period; inputting the aggregated ventilation rate to the baseline model; performing batch data analytics on the predictive model to update a building model; optimizing energy use to minimize actual energy cost based on the building model, energy cost information, and the data collected from the field sensors; generating energy savings data based on the baseline model and the actual energy cost.

Abstract: Methods and systems for identifying maintenance tasks in a building. An illustrative method may include capturing a plurality of images over time of a component of a building using an image capture device, comparing at least some of the plurality of images to a baseline image of the component to identify a physical change in the component, determining when the physical change in the component exceeds a threshold physical change, and sending a maintenance request to service the component when the physical change in the component exceeds the threshold physical change.

Abstract: A structure having convergence of a control system and a data analytics system. The control system may involve input-output models of items, for example, homes, buildings and process plants. The system may use sensor data and scientific principles to implement control models. The models may help to precisely achieve a desired value of a parameter. The data analytics system may involve analysis of diverse data and may create insights of the items. The control system plus the data analytics system may close the loop between insights and on-premise controls of the items represented by the input-output models. The control and data analytics systems may merge the best of both worlds to solve difficult issues pertaining to the items. The structure may be for comfort control, energy reduction, and so on, having improved performance based on the convergence.

Abstract: A structure having convergence of a control system and a data analytics system. The control system may involve input-output models of items, for example, homes, buildings and process plants. The system may use sensor data and scientific principles to implement control models. The models may help to precisely achieve a desired value of a parameter. The data analytics system may involve analysis of diverse data and may create insights of the items. The control system plus the data analytics system may close the loop between insights and on-premise controls of the items represented by the input-output models. The control and data analytics systems may merge the best of both worlds to solve difficult issues pertaining to the items. The structure may be for comfort control, energy reduction, and so on, having improved performance based on the convergence.

Abstract: A system and method obtain a database stored on a storage device containing information on multiple assets, the information including measurements taken from devices monitoring each asset, and context information corresponding to the environment the items are subjected to. The system and method groups assets via a computer system into a homogenous group as a function of selected context information and performs analytics via the computer system on the grouped assets to manage the assets.

Abstract: A computer implemented method includes providing information related to wind speed and direction prediction to a wind turbine energy prediction module, providing wind energy production prediction information to a resource allocation engine, and combining the wind energy production prediction information with information about non-renewable energy resources to provide an output identifying energy production resources to use for optimal load servicing.

Abstract: A system and method obtain a database stored on a storage device containing information on multiple assets, the information including measurements taken from devices monitoring each asset, and context information corresponding to the environment the items are subjected to. The system and method groups assets via a computer system into a homogenous group as a function of selected context information and performs analytics via the computer system on the grouped assets to manage the assets.

Abstract: An automated data processing method includes providing a plurality of incident data from a physical installation of a process automation system in a processing facility that collectively spans a period of time and building a stored relational database including database data from the incident data. The method includes automatically generating at least one processed data result from the database data, wherein the automatically generating generates at least one processed data result from the database data. The processed data result is in a displayable form that facilitates identification of a problem in the process automation system by an analyst in a remote support center.

Abstract: A method for online condition-based monitoring (CBM) of a tank farm including a plurality of storage tanks includes providing a tank model including a diagnostic and/or predictive tank model based on calculated tank metrics that is derived from historical data including tank operation data. The calculated tank metrics include tank operational metrics based on the tank operational data for the storage tanks and tank condition metrics based on tank inspection or maintenance data for the storage tanks. The tank model provides relationships between the tank condition metrics and the tank operational metrics. Results are generated using the tank model including at least one failure indicia for at least a first of the storage tanks using the calculated tank metrics and current measured data for the first tank as inputs to the tank model. The failure indicia is processed for scheduling at least one maintenance task for the first tank.

Abstract: A method (400) for automatically checking proposed adjustments by an individual to at least one parameter at a manufacturing plant includes (401) creating a proposed vector including at least one proposed entry from the individual. The proposed vector represents a proposed adjustment to the parameter. A database of historical vectors including the parameter is searched relative to the proposed vector, wherein a number ?0 of similar stored vectors is identified in the searching based on respective distances (d) relative to the proposed vector (402). If the number ?1, a distance measure R is calculated from the (d) for the similar stored vector(s) to indicate of how far or close the said proposed vector is to the similar stored vector (403). An alert is provided if the number=0 or R is above a predetermined threshold value (405). The method can be used for validation of proposed production planning parameters or process control parameters.

Abstract: A method for automatically monitoring the performance of equipment includes compiling current operating conditions associated with current conditions (PMc). A historical database including a plurality of stored operating conditions and associated stored performance measure (PM*) is searched, each stored operating condition including at least one stored sensor reading, wherein at least one similar operating condition is identified in the search using distances between the current operating conditions and the stored operating conditions. The performance measure (PM*) associated with the similar operating condition is fit to generate a regression model. The regression model is applied to the current operating condition to generate an estimate for the performance measure for the current operating condition (PMe). A difference between PMc and PMe is computed.

Abstract: Deviations associated with a process system are identified, such as by identifying deviations of process variables or production measurements from target values. A graphical display is generated that identifies at least some of the deviations and one or more characteristics associated with the deviations. For example, the graphical display includes a time axis, and each deviation is associated with a bar positioned in the graphical display to identify a start time and an end time of the deviation along the time axis. Also, each bar may include one or more indicators (such as patterns, colors, or shadings) that identify the one or more characteristics (such as an economic impact and/or a cause) of each deviation identified in the graphical display. In this way, a user can, among other things, identify when deviations from target values occur, durations of the deviations, and economic impacts and/or causes associated with the deviations.

Abstract: Methods (100), algorithms, and implementing systems (200) for guided annotation of process deviations by an individual responsible for annotations (e.g. process operator) for a manufacturing process having an associated computing system (210) including a historical database (stored in memory 219). The historical database is provided (101) including data associated with a plurality of process performance measures including stored deviations for the plurality of process measures, stored quantitative deviation attributes thereof and at least one cause associated with each of the stored deviations process performance measures. The method includes the individual responsible for annotation selecting at least one present deviation (D) to be annotated responsive to a deviation in a target process performance measure (T) selected from the plurality of process measures (102). Automatically, the stored quantitative attributes associated with D, T, and a target value or target interval for T are retrieved (103).

Abstract: A computer implemented method includes providing information related to wind speed and direction prediction to a wind turbine energy prediction module, providing wind energy production prediction information to a resource allocation engine, and combining the wind energy production prediction information with information about non-renewable energy resources to provide an output identifying energy production resources to use for optimal load servicing.

Abstract: A method for online condition-based monitoring (CBM) of a tank farm including a plurality of storage tanks includes providing a tank model including a diagnostic and/or predictive tank model based on calculated tank metrics that is derived from historical data including tank operation data. The calculated tank metrics include tank operational metrics based on the tank operational data for the storage tanks and tank condition metrics based on tank inspection or maintenance data for the storage tanks. The tank model provides relationships between the tank condition metrics and the tank operational metrics. Results are generated using the tank model including at least one failure indicia for at least a first of the storage tanks using the calculated tank metrics and current measured data for the first tank as inputs to the tank model. The failure indicia is processed for scheduling at least one maintenance task for the first tank.

Abstract: A method includes receiving at least one search parameter, where the at least one search parameter defines one or more restrictions on types of event patterns. The method also includes searching a collection of historical events associated with a process control system. The method further includes identifying one or more groups of alarms each having a pattern that satisfies the one or more restrictions. In addition, the method includes outputting information identifying the one or more groups of alarms. The method could also include receiving a selection of at least one of the one or more identified groups of alarms. The method could further include notifying one or more components in the process control system to begin dynamically suppressing alarms in the at least one selected group of alarms.

Abstract: A method for automatically monitoring the performance of equipment (100) includes the step (101) of compiling current operating conditions including at least one current sensor reading and at least one current performance measurement associated with the current conditions (PMc). A historical database including a plurality of stored operating conditions is searched (102), each stored operating condition including at least one stored sensor reading and at least one associated stored performance measure (PM*), wherein at least one similar operating condition is identified in the search using distances between the current operating conditions and the plurality of stored operating conditions. The performance measure associated with the similar operating condition is fit to generate a regression model (103). The regression model is applied to the current operating condition (104) to generate a model estimate for the performance measure for the current operating condition (PMe).

Abstract: A method (400) for automatically checking proposed adjustments by an individual to at least one parameter at a manufacturing plant includes (401) creating a proposed vector including at least one proposed entry from the individual. The proposed vector represents a proposed adjustment to the parameter. A database of historical vectors including the parameter is searched relative to the proposed vector, wherein a number ?0 of similar stored vectors is identified in the searching based on respective distances (d) relative to the proposed vector (402). If the number ?1, a distance measure R is calculated from the (d) for the similar stored vector(s) to indicate of how far or close the said proposed vector is to the similar stored vector (403). An alert is provided if the number=0 or R is above a predetermined threshold value (405). The method can be used for validation of proposed production planning parameters or process control parameters.

Abstract: Methods (100), algorithms, and implementing systems (200) for guided annotation of process deviations by an individual responsible for annotations (e.g. process operator) for a manufacturing process having an associated computing system (210) including a historical database (stored in memory 219). The historical database is provided (101) including data associated with a plurality of process performance measures including stored deviations for the plurality of process measures, stored quantitative deviation attributes thereof and at least one cause associated with each of the stored deviations process performance measures. The method includes the individual responsible for annotation selecting at least one present deviation (D) to be annotated responsive to a deviation in a target process performance measure (T) selected from the plurality of process measures (102). Automatically, the stored quantitative attributes associated with D, T, and a target value or target interval for T are retrieved (103).

Abstract: Deviations associated with a process system are identified, such as by identifying deviations of process variables or production measurements from target values. A graphical display is generated that identifies at least some of the deviations and one or more characteristics associated with the deviations. For example, the graphical display includes a time axis, and each deviation is associated with a bar positioned in the graphical display to identify a start time and an end time of the deviation along the time axis. Also, each bar may include one or more indicators (such as patterns, colors, or shadings) that identify the one or more characteristics (such as an economic impact and/or a cause) of each deviation identified in the graphical display. In this way, a user can, among other things, identify when deviations from target values occur, durations of the deviations, and economic impacts and/or causes associated with the deviations.